ANALYSIS OF ORGANOPHOSPHATE PESTICIDES IN THE BLOOD SAMPLES OF AGRICULTURAL WORKERS OF DISTRICT GUJRANWALA, PUNJAB.
______
SAFFORA RIAZ
______
DEPARTMENT OF ZOOLOGY LAHORE COLLEGE FOR WOMEN UNIVERSITY, LAHORE 2017 ANALYSIS OF ORGANOPHOSPHATE PESTICIDES IN THE BLOOD SAMPLES OF AGRICULTURAL WORKERS OF DISTRICT GUJRANWALA, PUNJAB.
______
A THESIS SUBMITTED TO LAHORE COLLEGE FOR WOMEN UNIVERSITY IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN ZOOLOGY
By SAFFORA RIAZ
______DEPARTMENT OF ZOOLOGY LAHORE COLLEGE FOR WOMEN UNIVERSITY, LAHORE 2017 CERTIFICATE
This is to certify that the research work described in thesis entitled “Analysis of organophosphate pesticides in the blood samples of agricultural workers of district Gujranwala, Punjab.” submitted by Ms. SAFFORA RIAZ to Department of Zoology, Lahore College for Women University has been carried out under our direct supervision. We have personally gone through the raw data and certify the correctness and authenticity of all results reported herein. We further certify that thesis data has not been used in part or full, in a manuscript already submitted or in the process of submission in partial fulfillment of the award of any other degree from any other institution or home or abroad. We also certify that the enclosed manuscript has been prepared under our supervision and we endorse its evaluation for the award of PhD degree through the official procedure of University.
______Supervisor Co Supervisor Prof. Dr. Farkhanda Manzoor Dr. Nasir Mahmood Head Department of Zoology Assistant Professor LCWU, Lahore Department of Biochemistry; Department of Date: Human Genetics and Molecular Biology University of Health Sciences, Lahore, Pakistan. Date:
Verified By Chairman
______Prof. Dr. Farkhanda Manzoor Head Department of Zoology Stamp:
______Controller of Examination Stamp Date: ______
DEDICATION
I WOULD LIKE TO DEDICATE ALL OF MY EFFEORTS TO MY FATHER RIAZ AHMED CHATTHA WHO SUPPORTS ME FINANCIALLY, MORALLY AND ENCOURGE ME TO EVERY STEP OF MY LIFE AND TO MY MOTHER GHULAM ZOHRA FOR HER PATIENCE ACKNOWLEDGEMENT
The whole praise to ALLAH Almighty the sovereign Power, the creator of the universe, who gave us knowledge, with which we are trying to understand the laws of nature and conquer the universe; who made me the super creature; blessed me with knowledge and enabled me to accomplish this task. I offer my humblest and sincere words of thanks to the Holy Prophet
Muhammad (PBUH), who is forever a torch of guidance for humanity.
I feel all words on the earth just failing to express my deep sense of gratitude to our respected
Vice Chancelor, Prof. Dr. Rukhsana Kausar for giving me opportunities to complete my research thesis of Ph.D Zoology. I respectfully express my deepest appreciation to our respected, distinguished and affectionate director research Prof. Dr. Shagufta Naz for providing opportunities to complete my research thesis.
I am also obliged to my supervisor Prof. Dr. Farkhanda Manzooor, Head of Zoology
Department, Lahore College Women University, Lahore for her sincerest guidance, critical suggestions. She has been so kind and supportive with her patience and knowledge and a source of inspiration for me. I respectfully express my deepest appreciation and acknowledgement to Dr. Nasir Mahmood, Assistant Professor, Department of Biochemistry;
Department of Human Genetics and Molecular Biology, University of Health Sciences,
Lahore, Pakistan for his keen interest, providing technical guidance, research facilities and valuable suggestions. I am highly thankful to my sister Sadia Tabassum and my brothers
Sami Ullah and Dr. Ali for encourage me to achieve this goal. I am also greatly indebted to my friends Saadiya Asma, Ayisha butt, Touseef Kazmi, Hafsa Memoona and Tehziba Kausar and my lab fellows for their friendly attitude, support and sympathetic encouragements. I also want to pay thanks to laboratory staff of Zoology Department of LCWU for their cooperation.
SAFFORA RIAZ CONTENTS
Title Page No.
List of Tables i
List of Figures ii
List of Abbreviations v
Abstract viii
Chapter 1 : Introduction 1
Chapter 2: Review of Literature 14
Chapter 3: Materials and Methods 48
3.1: Study design 48
3.2: Questionnaire based survey 50
3.3: Sample size 50
3.4:Sample collection and processing 50
3.5: Hematological analysis 50
3.6: Serological analysis 51
3.6.1: Alanine aminotransferase (ALT) 51
3.6.1.1: Procedure 51
3.6.2: Aspartate aminotransferase (AST) 52
3.6.2.1: Procedure 52
3.7. Biochemical analysis 53
3.7.1: Determination of cholinesterase activity 53
3.7.2: Acetylcholine Assay 53
3.8:Determination of levels of immunoglobulins 54
3.8.1:Protocol 54
3.9: High Performance Liquid Chromatography 55 3.9.1: Preparation of Standard of pesticides 55
3.9.2: Preparation of the serum sample 55
3.9.2.1: Protein Precipitation 55
3.9.2.2: Filtration assembly 56
3.9.2.3: Sonication 56
3.9.3: Optimization of condition for HPLC 56
3.9.4: Quntification of pesticides by HPLC 62
3.9.4.1: Area Height Method 62
3.10: Tuberculosis detection in suptum of spray workers 62
3.10.1: Molecular detection of tuberculosis 62
3.10.2: Genomic DNA isolation 63
3.10.3: Agarose gel electrophoresis of genomic DNA 64
3.10.3.1: Quantification of DNA 64
3.10.4: Preparation of 1% the agarose gel for PCR product 64 Analysis 3.10.4.1: Loading of the gel 65
3.10.5: Polymerase chain reaction 65
3.10.6: Molecular differentiation of M. tuberculosis and M. 68 Bovis 3.10.6.1: Gene clean of amplified DNA fragment for 69 sequencing 3.10.6.2: Sequencing of selected samples 69
3.11: Statistical analysis 69
Chapter 4: Results 70
4.1: Demographic features of agricultural spray workers of district 70 Gujranwala. 4.2: Educational level of workers by gender 71
4.3: Awareness and practices of pesticides use by gender 72 4.4: Personal equipment and clothing while spraying 73
4.5: Pesticides related acute health problems 75
4.6: Hematological profiles of agricultural spray workers 77
4.6.1: Complete blood profile of male agricultural spray 77 workers and non spray workers: 4.6.2: Complete blood profile of female agricultural spray 78 workers and female non spray workers. 4.7: Analysis of serological parameters of agriculture spray 80 workers 4.7.1: Liver enzymes ALT and AST analysis of male 80 agriculture spray workers in comparison to male non spray workers 4.7.2: Liver enzymes ALT and AST analysis of female 80 agriculture spray workers in comparison to female non spray workers: 4.8: Acetylcholinestrase standardization 82
4.9. Biochemical analysis of acetylcholinestrase 86
4.9.1. Analysis of level of acetylcholinestrase 86 concentration in blood serum of male spray workers 4.9.2. Analysis of level of acetylcholinestrase concentration in 87 blood serum of female spray workers 4.10: Immunoglobulin concentration in blood serum of male 88 spray workers 4.10.2: Level of immunoglobulin IgA 90
4.10.3: Level of immunoglobulin IgM 91
4.10.4: Levels of immunoglobulin IgE 92
4.11: Standaridization of HPLC 93
4.12: Pesticide residues detection and quantification blood 122 serum of spray workers 4.12.1: Descriptive statistical data of pesticides 123 quantification in serum samples of spray workers
4.13: Detection of different species of mycobacteria 124 4.13.1: DNA isolation and quantification 124
4.13.2: Molecular differentiation of M. tuberculosis 125 and M. bovis PCR with the use of primer set N & S. 4.13.3: Molecular detection of M. tuberculosis and M. 126 bovis in pesticides exposed workers. 4.13.4: Sequencing of targeted hup B gene 127
Chapter 5: Discussion 133
References 143
Annexures x
Plagiarism Report xxv
List of Publications and reprints xxvii
i
List of Tables
Table No. Title Page No. 3.9.3.1: HPLC conditions for the pesticides analysis in serum. 56 3.9.3.2: Optimized HPLC conditions for dichlorovos pesticide in blood serum of 57 agricultural workers. 3.9.3.3: Optimized HPLC conditions for profenophos pesticides in blood serum 58 of agricultural workers. 3.9.3.4: Optimized HPLC conditions for chlorpyrifos pesticides in blood serum 59 of agricultural workers. 3.9.3.5: Optimized HPLC conditions for malathione pesticides in blood serum of 60 agricultural workers. 3.9.3.6: Optimized HPLC conditions for imidacloprid pesticides in blood serum 61 of agricultural workers. 3.10.5.1. Concentration and volume of reagents used for PCR 66 4.6.1: Complete blood profile of male agricultural spray workers and non - 77 spray workers. 4.6.2: Complete blood profile of female agricultural spray workers and 78 corresponding female control subjects. 4.7.1: Comparison between liver enzymes ALT and AST in male agricultural 80 spray operators and corresponding controls. 4.7.2: Comparison between liver enzymes ALT and AST in female 80 agricultural spray operators and corresponding controls. 4.9.1: Acetylcholinestrase concentration level in male spray workers and their 86 corresponding control subjects. 4.9.2: Acetylcholinestrase concentration level in female spray workers and 87 their corresponding control subjects 4.10.1.1: Levels of immunoglobulin in blood serum of males agricultural spray 88 workers of exposed to pesticides as compared to non spray workers of district Gujranwala. 4.10.1.2: Levels of immunoglobulin in blood serum of females agricultural spray 89 workers of exposed to pesticides as compared to non spray workers of district Gujranwala. 4.12: Number of spray workers with positive concentration of pesticides. 122 Descriptive statistical data of pesticides residues detected in serum 4.12.1: samples of female spray workers. 123 4.12.2: Descriptive statistical data of pesticides residues detected in serum 123 samples of female spray workers. 4.13.3: Molecular detection of M. tuberculosis and M. bovis in pesticides 126 exposed workers.
ii
List of Figures Figure No. Title Page No. 1.1: Generic structural formula of OP insecticides. 2 1.2: Structural formula of some organophosphate insecticides. 3 1.3: Pathway of pesticides targeted biological markers. 6 1.6: Mechanism of AChE inhibition induced by OPs reactivation, 8 spontaneous hydrolysis, and aging of the phosphorylated enzyme 3.1: Map of District Gujranwala (Punjab, Pakistan) showing location of 49 the study area 3.10.5.2: Optimized condition of PCR (polymerase chain reaction) for (hup 67 B) gene amplification 3.10.6: Physical location of M and S primers used to detect M. tuberculosis 68 and M. bovis. 4.1: Age groups and percent population of agricultural spray workers 70 of District Gujranwala, Punjab, Pakistan. 4.2: Educational level and percent population of agricultural spray 71 workers of District Gujranwala, Punjab, Pakistan. 4.3: Awareness about use of pesticides and percent population of the 72 agricultural spray workers of District Gujranwala, Punjab, Pakistan. 4.4.1: Use of personal protective equipment and percent population of the 73 agricultural spray workers of District Gujranwala, Punjab, Pakistan. 4.4.2.a: Improper handling and direct exposure of a spray worker during 74 field application of a pesticide. 4.4.2.b: A spray worker in the field without using any personal protective 74 equipment (gloves, masks, handkerchief and boots). 4.5.1. Health hazards and percent population of agricultural spray workers 75 of District Gujranwala, Punjab, Pakistan.
4.5.2. a-f: Signs and symptoms of pesticides toxicity caused by direct 76 exposure to pesticides. 4.6.1: Graphical comparison (Box-Whisker Plots) of the following mean 79 hematological indices: WBC, RBC, HGB, HCT, MCV, MCHC, LYM, NEUT & PLT, between female and male pesticidal spray operators.
4.7.1: Graphical comparison (Box-Whisker plots) of mean ALT and AST 81 values between male and female pesticidal spray operators.
4.8: Relationship between acetylcholinestrase concentration and 82 fluorescence detected by fluorescence microplate reader at 560 ± 10 nm.
iii
4.8.1: Acetylcholinestrase activity of seven different concentrations 83 4.8.2-3: Acetylcholinestrase activity in blood serum based on colorimetric 84-85 assay principle 4.10.2: Levels of immunoglobulin IgA, among male and female spray 90 workers and non-spray workers (corresponding controls). 4.10.3: Levels of immunoglobulin IgM, in male and female pesticides 91 spray workers and their non-spray workers (corresponding controls). 4.10.4: Levels of immunoglobulin IgE among male and female spray 92 workers and their non-spray workers (corresponding controls). 4.11.1: Chromatogram of technical grade standard of dichlorovos analyzed 93 by reverse phase HPLC. 4.11.2: Chromatogram of technical grade standard of profenophos 94 analyzed by reverse phase HPLC. 4.11.3: Chromatogram of technical grade standard of chlorpyrifos analyzed 95 by reverse phase HPLC. 4.11.4: Chromatogram of technical grade standard of malathion analyzed 96 by reverse phase HPLC. 4.11.5: Chromatogram of technical grade standard of imidacloprid 97 analyzed by reverse phase HPLC. 4.11.6: Liquid chromatogram of blood serum of spray worker exposed to 98 pesticides show the detection of Chlorpyrifos. 4.11.7: Liquid chromatogram of blood serum of spray worker exposed to 99 pesticides show the detection of malathion. 4.11.8: Liquid chromatogram of blood serum of spray worker exposed to 100 pesticides show the detection of Malathion. 4.11.9: Liquid chromatogram of blood serum of spray worker exposed to 101 pesticides show detection of Profenophos. 4.11.10: Liquid chromatogram of blood serum of spray worker exposed to 102 pesticides show detection of Imidacloprid. 4.11.11: Liquid chromatogram of blood serum of spray worker exposed to 103 pesticides show the detection of malathion. 4.11.12: Liquid chromatogram of blood serum of spray worker exposed to 104 pesticides show the detection of residues of many pesticides. 4.11.13: Liquid chromatogram of blood serum of spray worker exposed to 105 pesticides show the detection of profenophos. 4.11.14: Liquid chromatogram of blood serum spray worker exposed to 106 pesticides show the detection of malathion. 4.11.15: Liquid chromatogram of blood serum of spray workers exposed to 107 pesticides show detection of residues of several pesticides. 4.11.16: Liquid chromatogram of blood serum of spray worker exposed to 108
iv
pesticides show the detection of residues of several pesticides. 4.11.17: Liquid chromatogram of blood serum of spray worker exposed to 109 pesticides show the detection of chlorpyrifos. 4.11.18: Liquid chromatogram of blood serum of pray worker exposed to 110 pesticides show the detection of chlorpyrifos. 4.11.19: Liquid chromatogram of blood serum of spray worker exposed to 111 pesticides show the detection of malathion. 4.11.20: Liquid chromatogram of blood serum of male spray workers 112 exposed to pesticides show detection of malathion. 4.11.21: Liquid chromatogram of blood serum of spray worker exposed to 113 pesticides show detection of imidacloprid. 4.11.22: Liquid chromatogram of blood serum of spray worker exposed to 114 pesticides show detection of residues of several pesticides. 4.11.23: Liquid chromatogram of blood serum of spray worker exposed to 115 pesticides show detection of dichlorovos. 4.11.24: Liquid chromatogram of blood serum of spray workers exposed to 116 pesticides show the detection of residues of several pesticides. 4.11.25: Liquid chromatogram of blood serum of male spray workers 117 exposed to pesticides show detection of malathion. 4.11.26-29: Representative Liquid chromatogram of blood serum of non spray 118-121 workers (control group). 4.13.1: Representative photograph showing DNA isolation from sputum 124 culture samples. 4.13.2: Agarose gel (1.5%) showing differentiation of M. tuberculosis and 125 M. bovis by PCR using primer set M and S. 4.13.4: Multiple sequence alignment of histone like protein (Hup B) gene. 132
v
List of Abbreviations
AChE Acetyl cholinesterase enzyme
ADI Acceptable daily intake
ALP Alkaline phosphatase
ALT Alanine aminotransferase
ANOVA Analysis of variance
AST Aspartate aminotransferase
BChE Butrylcholinesterase
BMI Body mass index
BSA Bovine serum albumin
BUN Blood urea nitrogen
CI Confidence of interval
CM Carbamate
Con A Concanavalin A
CV Coefficient of variation
DAP Dialkyl phosphate
DEET N, N-diethyl-m-toluamide
DMTP Dimethiotriphosphate
DNA Deoxyribo nucleic acid
DTNB 5,5'-dithiobis-(2-nitrobenzoic acid)
ECD Electron capture detector
ECG Electrocardiogram
ELISA Enzymes linked immunosorbent assay
ESR Erythrocytes sedimentation rate
G6PD 6-phosphate dehydrogenase
vi
GC-ECD Gas chromatography coupled with electron capture detector
GC-MS Gas chromatography / mass spectrometry
GC-NPD Gas chromatography analysis with nitrogen phosphorus detection
GOD Enzyme glucose oxidase
GOT Glutamate oxaloacetate transaminase
GPT Glutamate pyruvate transaminase
Hb Hemoglobin
HDL High density cholesterol
HIV Human immune deficiency virus
HPLC High performance liquid chromatogramy
HRP Horse raddish peroxidase
Ig Immunoglobulines
LC/MS/MS Liquid chromatogramy tandem mass spectrometry.
LDH Lactate dehydrogenase
LDL Low density cholesterol
LOD Limit of detection
LOQ Limit of quantification
M. bovis Mycobacterium bovis
MAS-PCR Multiplex allele specific polymerase chain reaction
MCH Mean corpuscular hemoglobin
MCHC Mean corpuscular hemoglobin concentration
MCV Mean corpuscular volume
MSD Mass selective detectors
MS-MS Tandem mass spectrometry
MTB Mycobacterium tuberculosis
MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide
vii
NOELs No-observed effect level
NPD Nitrogen-phosphorus detector
OELs Occupational exposure limits
OP Organophosphate
OPH Organophosphorus hydrolase
PBMC Peripheral blood mononuclear cells
PBS Phosphate buffer saline
PCR Polymerase chain reaction
PLT Platelets
PON1 Paraoxonase polymorphism
PPE Personal protective equipment ppm Part per million
RBC Red blood cells
RSD Relative standard deviation
RT Retention time
SIM Selective ion mode
SOD Superoxide dismutase
SPME Solid-phase headspace microspace
SPSS Statistical Package for Social Sciences
TB Tuberculosis
TNB 2-nitro-5-thiobenzoate
WBC White blood cells
WHO World health organization
ZN Ziehl-Neelsen
viii
ABSTRACT
Numerous health disorders are associated with human occupational exposure to organophosphate (OP) pesticides and these pesticides impose serious public health problems. Agricultural workers are at high risk of exposure to hazards of OP pesticides. Evaluation of the pesticide effects on hematological, serological and immunological parameters is necessary to determine the adverse effects of excessive use of pesticides. In the present study complete blood count, liver enzyme level, acetylcholinestrase activity, serum immunoglobulin, pesticides residues level, and molecular detection of tuberculosis among agricultural workers of District Gujranwala, Punjab, Pakistan, were investigated. Data were collected through questionnaires from 200 professional agricultural spray workers and 100 agricultural non-spray workers (control) ranging in age between 20 to 60 years. The most commonly reported signs and symptoms were feeling of vomiting (males 22%, females 42%) and skin irritation (males 32%, females 28%) after spraying. Generally, inadequate protective measures were observed by these pesticidal spray workers : only 16.5% male and 32% female workers used gloves while 12.5% males and 6% females used face masks during their field spray work. The blood parameters, such as hemoglobin, hematocrit, MCV, MCH, MCHC, of spray workers and non-spray workers were also investigated. WBC and RBC levels of male sprayers and non-sprayers were statistically significantly (P < 0.05) different. In female spray workers, the WBC and neutrophils levels were significantly different as compared to non-spray workers. Overall, in both male and female pesticides-exposed spray workers, mean values of ALT and AST were higher as compared to non- exposed workers. This research revealed abnormal level of acetylcholinestrase (AChE) due to the exposure to multiple pesticides; serum AChE activity level was reduced in male as well as female spray workers as compared to the corresponding control subjects. Mean unit value of AChE in male spray workers was 0.16 U/ mL (min = -0.10 U/ mL and max = 0.66 U/ mL) and in non-spray workers was 0.44 U/ mL (min =0.01 U/ mL and max = 0.93 U/ mL); these values were significantly (P < 0.05) different statistically. Similarly, highly significant differences (P< 0.05) was observed in female spray workers, i.e., 0.41 U/ mL (min = 0.06 U/ mL and max = 0.93 U/ mL) and non-spray workers : 0.65 U/ mL (min =0.32 U/ mL and max = 1.1 U/ mL).
ix
Immunotoxicity in spray workers with a significant difference of IgA and IgM (P = 0.033 and P = 0.000) in male spray workers and non-spray workers, respectively, was also observed. Significant differences of immunoglobulin IgM and IgA (P = 0.000) and P = 0.000) were also observed in female spray workers and non-spray workers. Non-significant difference was observed for IgE (P = 0.928) level in male spray workers and non-spray workers. Likewise, non-significant difference was also observed for IgE (P= 0.425) levels in female spray workers and non-spray workers. Molecular detection of Mycobacterium tuberculosis (M. tuberculosis) and Mycobacterium bovis (M. bovis) was carried out by targeting histone-like protein (hupB) gene in cultured sputum samples of spray workers. Mycobacterium tuberculosis was detected in 15% male sprayers and 36% female sprayers, while M. bovis was detected in 5% male sprayers and 10% female sprayers. A chi-square test indicated that a significant difference (P < 0.05) existed between positive and negative M. tuberculosis and M. bovis in both male and female spray workers. The susceptibility of pesticides-exposed spray workers to tuberculosis and alterations in hematological and liver enzymes is crucial for health. Results indicated that blood serum samples of spray workers were contaminated with various OPs. Among spray workers (n=200) the OP insecticide, chlorpyrifos, was detected in 18 (12%) male blood serum samples and 7 (14%) female blood serum samples, whereas profenophos was detected in 9 (6%) male serum samples and 3(6%) blood serum samples of females spray workers. Pesticides residues of imidacloprid were detected in 25 (16.6%) males and malathion in 13 (8.6%) males and 3 (6%) females, while dichlorovos was detected in 2 (4%) females. The OP pesticides detected in the serum samples of spray workers were chlorpyrifos (1.4μg/L), profenophos (1.29 μg/L), imidacloprid (0.14 μg/L) and malathion (1.40 μg/L); dichlorovos was not detected in male spray workers. In female spray workers, chlorpyrifos (1.39 μg/L) profenophos (1.23 μg/L), and malathion (1.40 μg/L) and dichlorovos (0.03 μg/L) were detected but imidacloprid was not detected in blood serum of spray workers, respectively. From the results of the present study it can be concluded that frequent use of highly toxic pesticides, inadequate or no use of personal protective equipment and poor hygienic practices are the main reasons for the symptoms of pesticides toxicity in spray workers.
1
INTRODUCTION
Pakistan is basically an agricultural country with nearly 70% of the country’s population inhabiting in villages and is directly or indirectly involved in agriculture. To save crops from attack of a variety of pests and increase per acre crop yield, farmers commonly use a variety of costly and hazardous, synthetic pesticides for killing and eliminating rodents, fungi, insects, and weeds in the developing as well as in the developed countries (Kamel and Hoppin, 2004; Mnif et al., 2011). These pesticides include a wide range of chemical compounds, such as insecticides, fungicides, herbicides, rodenticides, molluscicides, nematicides, and plant growth regulators, etc. (Saxena and Saxena, 2010; Aktar et al., 2009). The frequent and extensive field use of pesticides is of great environmental concern because of the associated possiblility of health hazards to human beings as well as wild and domestic animals (Alpalan et al., 2006).
The District of Gujranwala in Punjab, Pakistan, is an important crop cultivation belt of Pakistan. Previous surveys in various villages of this District revealed that a large number of the villagers in Gujranwala District comprise of subsistence farmers. Crops, such as wheat, cotton, rice are irrigated in thisDistrict by canal water (Ullah et al., 2008). These crops are grown with rather excessive applications of synthetic pesticides that are known to cause various problems, such as chemical pollution, resistance in target pests as well as their accumulation (residues) in animals and human beings (Azmi et al., 2009). In recent years, usage of pesticides has been increasing steadily, and at present, more than one thousand pesticides are used in the world. In India, 15-20% of the total cultivated crops are destroyed due to attack by pests;. These pests become resistant to pesticides because of the uncontrolled use of pesticides by the Indian cultivators (Khan, 2012). Moreover, pesticides applied in the field usually disperse in the environment and are liable to affect the health and safety of most spray workers in the field (Hashmi and Dilshad, 2011).
Throughout the world, use of pesticides has increased to enhance food production for fulfilling the requirement of the ever-increasing human population (Shinnawy, 2008). In 2003, about 890 total active ingredients of pesticides were registered as pesticides in the USA (Bolognesi, 2003). The pesticides-related major economic and environmental losses in the USA are due to their excessive application in the public 2 sector resulting in wide-spread and pervasive human exposure (Pimentel et al., 2005).. Continuous exposure of humans to pesticides can result in accumulation of pesticides in human body resulting in impairment of human health. In the USA, 18 cases of pesticides-related illness had been reported among every 100,000 workers due to occupational exposure to pesticides (Calvert et al., 2004).
In the past few decades, the use of pesticides in general has been increasing exponentially in Pakistan. For example, in the agricultural sector about 254 metric tons of pesticidal chemicals were imported in 1954; however, utilization of pesticides in the country had increased to more than 7,000 tons per year in the era of 1960-70s (Tariq et al., 2007). World-wide use of pesticides, including herbicides, insecticides, fungicides and rodenticides increased to approximately 2.4 million tons in both 2006 and 2007 (Grube et al., 2011).
In Spain, the highest amount of pesticides sold and used nationwide for the year 2010 was 93,252 tons, withh. Andalusia Province of Spain ranking first where almost 24% of the total pesticides were used for intensive farming in plastic greenhouses (Parron et al., 2014).
Organophosphate (OP) insecticides were developed during the early 19th century; however, their effects on insects are similar to their effects on humans. OP insecticides are esters of phosphoric and phosphorothioic acid that exist in two forms: (i) Thione (sulfur containing)
(ii) Oxon (oxygen containing).
The oxon OPs are more toxic than thione OPs. However, thione OPs readily undergo conversion into oxon (Ladou, 2004). The generic structural formula of OPs is given below in Figure 1.1.
Figure 1.1: Generic structural formula of OP insecticides 3
OP compoundsare generally used to control vector-borne diseases and also play an essential role in meeting the demand of food, cotton and fiber of ever-increasing human population. However, health of a vast majority of industrial and agricultural workers gets affected by the OPs that disperse in the environment after field application. Hashmi and Dilshad (2011) had reported that spray workers were directly exposed to pesticides at work places through air and drinking water in pesticides- contaminated environment and also while mixing and handling of sprays, eating food and smoking. In some cases, pesticide residue concentrations of these compounds in blood samples of workers may lead to a variety of serious diseases and metabolic and systemic dysfunctions. Magnitude of occupational exposure to pesticides in agricultural spray workers is higher than that of the general population (Khan et al., 2013).
OPs include insecticides, such as malathion, diazinon, chlorpyrifos, azamethiphos, dichlorvos, parathion and methyl parathion (Athanasopoulos et al., 2004). Structural formulae of some OPs are given below in Figure 1.2.
Profenofos Chlorpyrifos
Malathion Dichlorvos
Figure 1.2: Structural formula of some organophosphate insecticides 4
The unregulated and excessive use of OP compounds to control insect pests has become thought-provoking. In developing countries, exposure to pesticides is one of the occupational risks among spray operators (Wesseling et al., 2001). These operators are exposed to pesticides by different path ways, i.e., dermal, oral, respiratory and conjunctival routes (Hoppin et al., 2006). Solid pesticides tend to have less chance of entry into human body but their liquid or gas forms can be easily absorbed into the body through all three routes of entry (Berthet et al., 2014). Superficial area of human skin is undoubtedly the major consideration of accidental acute exposure as a result of splashes and spills when handling (mixing, loading or disposing) pesticides. Similarly, pesticides in the form of vapors, particles, or aerosols are absorbed through respiratory tract very efficiently (Coronado et al., 2004).
The degree of hazard of pesticides through dermal absorption depends upon the composition of pesticides, the duration of exposure, and the patricide- pescontaminated body part(Baldi et al., 2006). Pesticides toxicity may be minimized when diluted sprays are applied with special conventional spraying equipment that produces droplets of small sizes. By contrast, the potential for respiratory exposure increases when concentrated materials are used and larger droplets are produced using high volume application equipment (Sarwar, 2015).
Once the pesticides get absorbed into the blood stream they are readily distributed into the entire body affecting various organs. Exposure to even very small amount of an OP compound can be fatal; death is usually caused by respiratory failure resulting from paralysis of the diaphragm and intercostal muscles, depression of the brain respiratory center, bronchospasm, and excessive bronchial secretion (Jokanovic and Prostran, 2009). However, for crops, pesticides may entail a number of benefits by controlling the risks and problems caused by pests (Konradsen et al., 2003). When synthetic pesticides are used indiscriminately without considering environmental dissipation they cause health hazards. Workers are indirectly exposed to pesticides while eating with hands unwashed after work as well as while spraying (Wilson and Tisdell, 2001) and as a result of deposition of these residues in their body, they may suffer from chronic and acute diseases, such as vomiting, nausea, headache, and various health hazards (Venkataramana and Sankararaman, 2005). 5
Chemical and toxicological properties of OP insecticides are the actual risk factor for the agricultural spray operators; however, the actual risk assessment is difficult to measure. Exposure may be accidental or occasional having subsequent bad affect on the health of operator (Ajayi and Akinnifesi, 2008). In developing countries, the major reason for the relatively high incidence of pesticides poisoning has been the use of pesticides without any legislative framework (Konradsen et al., 2003). Jindal et al. (2007) stated that long-term exposure to low level of pesticides targeted organs non- specifically and eventual health outcomes of spray workers were hard to be diagnosed. Exposure profile of spray operators to pesticides manifest an array of clinical problems, physico-chemical and toxicological signs and symptoms due to high frequency use of pesticides as well as inappropriate method(s) of application without use of personal protective equipment (Del Prado-Lu, 2007; Nerilo et al., 2014). Prolonged exposure to OP pesticides altered hematological profile and also caused hepatotoxicity in humans used as biological markers (Figure 1.3.).
Blood parameters, such as hemoglobin, hemocratict, white blood cells, leucocytes count, neutrophils count, mean corpuscular volume changed due to exposure to pesticides (Dasgupta et al., 2007). Biochemical parameters transformed due to low level of pesticides exposure that cause liver dysfunction and adverse biochemical changes in human (Elhalwagy and Zaki, 2009; Ibrahim et al., 2011). Chronic and acute poisoning of OPs in pesticides-exposed spray operators may cause thrombocytopenic purpura and aplastic anemia (Al-Sarar et al., 2009).
Hepatocellular necrosis was specifically caused by alteration in the aminotransferase. Keto group of ketoglutaric acid are the product of the enzymes-aspartate aminotransferase (AST) and alanine amino transferase (ALT) catalysis that transferred the amino acids of aspartate and alanine, respectively. A variety of pesticides are detoxified by the liver enzymes due to their specificity to the number of substrates (Thapa and Anuj, 2007).
Acetylcholinestrase (AChE) enzymes are involved in the release of acetylcholine at the nerve endings and the action of these enzymes is inhibited by OP insecticides in the pesticides-exposed agricultural workers; neural transmission is depolarized by the increased cholinergic effects in the human body (Roldan et al., 2006).
6
Figure 1.3: Pathway of pesticides targeted biological markers (Aprea et al., 2002)
7
Organophosphate insecticides are considered as the cholinesterase inhibitors, so to monitor the extent of toxicity of OPs, AChE activity level in blood serum. Butrylcholinesterase (BChE) activity in plasma ever be used as biomarkers to determine the extent of exposure of OPs. There was direct correlation between the Ops and the AChE activity therefore it was considered as the most reliable biomarkers (Pathak et al., 2011). The OPs inhibit the activity of AChE enzyme as shown in Figure 1.4 by inactivating the voluntary nerves and autonomic nerve endings and parasympathetic nerves. This inactivation results into accumulation of acetylcholine, a neurotransmitter during nerve impulse, and reduces the over activation of the neurons at the neuromuscular junction. Due to this imbalance of cholinesterase enzyme activity, nerves cannot perform their normal function; nerves continuously send messages to the body that may lead to weakness and twitching of the muscles (Joshaghani et al., 2007).
OPs are direct or indirect AChE inhibitors generally lipid soluble and do not persist in the environment. Repeated exposure to OPs in spraying season in small dose over time had additive effects and may finally cause poisoning and victims may have “fits” or convulsions and may even die. In case of mild spray exposures, workers felt fatigue, headache, and dizziness, while inability to walk, weakness and chestailments were caused by the moderate poisoning. Severe toxicity of OPs leads to unconsciousness, severe constriction of pupils and muscle twitching ultimately resulting in death (Panda and Nanda, 2011). Depressed level of AChE by OPs caused neurological impairment. Low exposure index level of residues also caused acute and chronic disorders in spray workers (Mekonnen and Ejigu, 2005).
For the environmental monitoring, industrial analytical technology, pharmaceutical agriculture sector and many other health care sectors broad field of extremely sensitive biosensors were developed. Biosensors are required for the detection of limit of food contaminants, environmental pollutants most sensitive biosensors have been applied into medical field (Patel, 2002).
8
Figure 1.6: Mechanism of AChE inhibition induced by OPs reactivation, spontaneous hydrolysis, and aging of the phosphorylated enzyme (Colovic et al., 2013).
9
For the detection of the target compounds biosensors are used as analytical devices. Biosensors tightly bind with the physical transducers for recognition of target elements (pesticides or other environmental pollutants) in the biological samples. As a result, bonding between analyte and bioreceptors is transformed into a measurable signal for the bio-recognition of the targeted compound (Thevenot et al., 2001).
Biosensors have become the attracted tool for detection of extraordinary chemical and biological components. They have exceptional performance capabilities, for instance, high specificity and sensitivity, fast response, low cost, relative compact size and user-friendly operation (Banica, 2012).
The biosensors contain the enzyme, glucose oxidase (GOD), attached to the surface of an amperometric oxygen electrode which directly quantifies the amount of blood glucose by the electrode-based on the oxidation of glucose to gluconic acid (Clark and Lyons, 1962).
The traditional methods for determining an insecticide in a medium are gas chromatography (GC) or high performance liquid chromatography (HPLC) coupled with mass selective detectors (MSD) (Schulze et al., 2002a). The main disadvantage of these systems is the need for high price equipment and highly qualified technician(s) to operate them. These methods are not only expensive but also time consuming and not portable. Thus, other methods have been developing for better biosensor platforms. In amperometric biosensor developments; butrylcholinesterase, OPs hydrolase, alkaline and acid phosphatase, ascorbate oxidase, acetolactate synthase and aldehyde dehydrogenase enzymes can also be used in addition to AChE since all of these enzymes are inhibited by the pesticides (Trojanowicz, 2002).
Acetylcholinesterase is used to develop a disposable screen-printed biosensor as compared to the traditional analytical methods (Schulze et al., 2002b). Although this biosensor is based on easier method than the conventional counterparts, need of a screen printer limits its usage as a portable biosensor. Potentiometric measurements of pesticide detection are similar to amperometric detection but both are electrochemical sensors. In potentiometric biosensors, OP hydrolase (OPH), a biological catalyst is used effectively to hydrolyze a range of OPs esters, pesticides, such as parathion, coumaphos and acephate, and chemical warfare agents, such as soman, sarin, VX, and tabun (Mulchandani et al., 1998). 10
The colorimetric pesticide biosensors are basically based on an artificial substrate acetylcholine that cleaved with AChE, target of insecticides for inhibition. After cleavage, free thiols of artificial substrate react with DTNB ((5,5'-dithiobis-(2- nitrobenzoic acid) in order to produce a colorful TNB(2-nitro-5-thiobenzoate ) reagent. If there are no insecticides present, reaction shows yellow color formation and if the sample is contaminated with insecticide, AChE is inhibited and no reaction occurs (Nagatani et al., 2007).
A pesticides upto two ppm concentration (part per million) detected by the physical adsorption of the enzyme on DZN-oxon biosensors but their shelf-life was insufficient (Luckham et al., 2009). Indophenylacetate, 2,6-dichloroindophenyl acetate, and indoxyl acetate molecules used as biosensors based on colorimetric method (Kim et al., 2006).
Worldwide, a range of products of different pesticide groups have been examined for their toxic end points. Biological examinations concerning pesticide exposures could be conducted by investigating whole main compound(s) or their metabolites in urine, serum, whole blood, or plasma (Aprea et al., 2002).
In the developed countries, gas chromatography coupled with electron capture detector (GC-ECD) is used for determination of residues of toxic pesticides (and their major metabolites in human serum or urine samples) and their growing effect on humans (Cruz et al., 2003), as well as gas chromatography-mass spectrometry (GC- MS) (Weiyue et al., 2010; Hayat et al., 2010) high pressure liquid chromatography coupled with ultraviolet detector (HPLC-UV) (Azmi et al., 2006), liquid chromatography-ionspray-mass spectrometry or liquid chromatography tandem mass spectrometry (LC/MS/MS). Some of these methods comprise of laborious and time- consuming extraction and dervitization protocols which are difficult to adopt in emergency cases of severe poisoning. Therefore, it is imperative to develop selective, reliable and rapid methods that can be helpful in the identification and quantification of as many pesticides as possible in human biological fluids (Araoud et al., 2010).
Low education levels of the rural populations, lack of information and training on pesticide safety, poor spraying technology, and inadequate personal protection during pesticide use play a major role in the intoxication scenario (Hurtig et al., 2003). In general, knowledge of the main determinants of pesticide exposure in developing 11 countries is often poor and also exposure situations may differ among countries (Atreya, 2008).
Chronic low-level exposure to pesticides is associated with serious health problems including metabolism impairment, neurotoxicity, and carcinogenicity, reproductive and endocrine disruption as well as immune dysfunctions (Corsini et al., 2008). The immune system is host defense system comprising many biological structures and processes within an organism to protect against diseases. There are considerable evidences that widely used pesticides may suppress immune response to bacteria, viruses and making people significantly more vulnerable to diseases. Epidemiological evidences have indicated the prevalence of disease associated with alteration in immune response. Pathogens can rapidly evolve and adopt and thereby avoid detection and neutralization by immune system (Diaz-Resendiz et al., 2015).
People with compromised immune systems are most at risk of developing active tuberculosis (TB). Tuberculosis is caused by bacteria Myobacterium tuberculosis that most often affects the lungs, although it can also affect other organs, such as the kidneys and heart. TB can either be active or latent (where no symptoms occur, and the condition cannot be passed on). TB is an airborne pathogen, meaning that the bacteria that cause TB can spread through the air from person to person (Wang et al., 2015).
Tuberculosis is directly related to the number of droplet nuclei carrying M. tuberculosis that are expelled into the air by the infected persons. Depending on the environment, these tiny particles can remain suspended in the air for several hours. Mycobacterium tuberculosis is transmitted through the air. Infection occurs when a spray worker inhales droplet nuclei containing M. tuberculosis, and the droplet nuclei traverse the mouth or nasal passages, upper respiratory tract, and bronchi to reach the alveoli of the lungs (Negi et al., 2005). Bovine TB is becoming increasingly important due to the susceptibility of humans to the disease caused by M. bovis and there is evidence that M. bovis infections may be more significant than generally considered (Senthil et al., 2014). The agricultural occupation is associated with an increased risk of TB because it attracts workers in a high-risk category for TB since most of them have poor nutritional status and live in poor housing conditions (Faria et al., 2006). Humans usually acquire TB infection from their immediate environment and from the animal source. However, there is a real risk that agricultural workers living in closer 12 contact with cattle may acquire the infection from them. Because agricultural work takes place in rural areas, farmworkers are exposed to organic and mineral dusts, animal and plant dusts, toxic gases, molds and other respiratory irritants. All of these have been associated with respiratory illnesses, such as asthma and chronic bronchitis (Radon et al., 2002).
The aim of the present study was to analyze harmful effects of pesticides on blood indices and determine biochemical changes in liver enzymes, analysis of AChE level, immune-toxicity, and prevalence of TB among workers routinely using agricultural pesticides. Correlation of some blood parameters of individuals regularly exposed to pesticides has been previously reported from different countries. In Pakistan, some comprehensive work on this aspect was conducted previously in Karachi, by Khan et al. (2000). However, due to rather extensive and frequent use of pesticides in the agricultural sector in the Guranwala District of Punjab, there was a dire need to explore health status of workers frequently handling agricultural pesticides in the District because this District is overwhelmingly agricultural and In the District of Gujranwala, information on the impact of pesticides on health aspects of farm workers frequently handling and dealing with pesticides is lacking. The present study was needed to generate this information to document health risks to humans (farmers, pesticides vendors and field spray labor) associated with exposure to pesticides with ultimate goal of minimizing these health risks to the farming community in general. In this context, it was deemed absolutely necessary to inform and train vegetables and other crops growers regarding safe handling and use of pesticides by organizing training programs for updating and strengthening the skills of the farming community in terms of efficient pest management. With this objective in mind the present study was designed to understand the existing knowledge of vegetable growers concerning the pesticides they were handling and using frequently and identify and prioritize their training needs regarding safe use of pesticides. The findings of the study also provide guidelines to researchers, scientists, health practitioners in the District regarding use of pesticides and related health hazards. Overall, this research should help in developing strategies for prevention and control of pesticide poisoning to farming community at large through careful and protective use of pesticides, equipment and related tools in Pakistan.
13
AIMS AND OBJECTIVES
The aim of this research was to investigate the adverse impact of pesticides on health of pesticides spray operators in the District of Gujranwala, Punjab, Pakistan. Base-line information was needed to be generated so that risk exposure and adverse health effects on the spray workers could be minimized. The specific objectives of the study were:
Assess knowledge, attitude and safety practices used by spray workers with respect to possible adverse health effects of pesticides on them in District Gujranwala.
Compare hematological profile and blood cholinesterase enzyme level of spray workers and healthy unexposed (to pesticides) control group.
Determine correlation of exposure to pesticides with hepatotoxicity by estimating the liver enzymes levels in both spray workers and healthy control individuals.
Analyze pesticides (primarily OPs) residues in blood sera of pesticides- exposed spray workers in comparison with healthy unexposed controls.
Elucidate immune-toxicity by ELISA and prevalence of tuberculosis among spray workers by molecular detection method in comparison with healthy controls.
14
REVIEW OF LITERATURE
Organophosphorus (OP) insecticides are widely used for the control of agricultural pests, against disease vectors as well as for household and domestic use purposes. Although there are many benefits of using these insectides, they are also harmful to humans, mainly children. It has been estimated that about 1 to 5 million cases of pesticide poisoning occur every year, resulting in about 20,000 deaths. Most of these poisonings occur in developing countries, where safeguards are often inadequate or deficient (Eddleston, 2000). Although the incidence of severe acute organophosphorus pesticide poisoning is much less in developed countries, many patients with acute low dose unintentional or occupational exposures present to health amenities (Roberts et al., 2005; Lai et al., 2005).
George et al. (1961) determined a photometric method for extracts of AChE activity, tissue homogenates, and cell suspensions. Enzymatic activity is measured by following the increase in yellow color produced from thiocholine upon reaction with the dibobisnitrobenzoate ion. The method was used to study the enzyme in human red blood cells and brain homogenates, kidneys, lungs, liver and muscle tissue of rats. The kinetic constants determined by this system for erythrocyte cholinesterase were presented. The data obtained with AChE as substrate were similar to those of acetylcholine.
Itoh et al. (1996) described the object and benefits of high-proformance liquid chromatography (HPLC) combined with atmospheric pressure chemical ionization mass spectrometry used in the study of pesticide compounds for 21 different types of OP and 8 different N-methylcarbamate types. The two ions (positive and negative) were identifying the OP pesticides. However, 8-N-methylcarbamate pesticides had been recognized only by positive ions. Compared to electron impact mode, the spectra obtained by this method showed a pattern that was simple and easy; the mass spectra were sufficiently different for anonymous peak identification in the chromatogram. With the great specificity of this method through an extremely easy pre-processing process, it could do a quick analysis.
Misra et al. (1994) reported the cognitive clinical and neurophysiological changes due to chronic occupational exposure to OP pesticides. The mean age of the workers in their study was 32.1 years (range 19-55 years) while the mean duration of exposure 15 was 10.5 years. The workers had suffered from mild transient symptoms after spraying. There was no clinical evidence of excessive cholinergic activity. Serum AChE level was 27% less in the pesticides-exposed group compared to the control group. Eevent-related potentials were elicited in 28 subjects and latency was prolonged in one subject only but the group difference was significant. It was suggested that chronic exposure to fenthion had subtle subclinical effect on the cognitive functions and potentials of agricultural workers.
Mukund and Sheela (1996) conducted a study in the Pune District, India, and discovered the incidence of one in three cases of TB in the hired farm laborers. In another study of agricultural workers in Uttar Pradesh, India, one in five workers suffered from respiratory diseases and one fifth of respiratory diseases were due to pulmonary TB. In the survey conducted in the central district of Wardha, Maharashtra, India, it was found that 42% of the rural population was engaged in agriculture-related activity for 5 years. About 85% of the working population in rural areas and 20% in urban areas were involved in agriculture-related activities.
Wesseling et al. (1997) reported that large populations of third world workers are exposed to pesticides, including those pesticides strictly regulated and banned in industrialized countries. Studies of knowledge, attitudes and practices indicate that safe use of pesticides is the rule in third world countries. The few studies on chronic health outcomes show neurotoxic, reproductive and dermatological effects. Exposure assessment consists mainly of cholinesterase tests, and few studies have quantified dermal and respiratory exposure. It was demonstrated that there is need to assess the prevention measures and policies. There is no evidence that widespread "safe use" programs have greatly affected exposure and morbidity. It was concluded that research should focus on simple methods for monitoring exposure and surveillance of acute disease and its causes in order to develop and evaluate rapid local interventions.
Franz et al. (1999) found that the activity of erythrocytes AChE is the appropriate tool for the diagnosis of exposure and OP poisoning. The original Ellman colorimetric procedure was disturbed by strong absorption of hemoglobin at 412 nm. Altered wavelength method was modified to 436 nm. This reduced indication of absorption to 80% and absorption of hemoglobin to 25%. The natural noise relationship is further improved by reducing the pH concentration and the substrate, thus allowing the residual activity to be measured by 3%. AChE activity was determined in whole blood 16 samples in the presence of a selective inhibitor of butyryl cholinesterase thopropazine. The dilution of blood samples (1: 100) stops the side reactions in the presence of an inhibitor (OP) and reactivating (oxime). The standardization activity AChE hemoglobin content determined as cyanmethemoglobin, avoid dilution errors. This modified approach provides a simple way for sensitive and accurate determination of AChE activity in whole blood in the presence of OPs, even with low-tech equipment.
Storm et al. (2000) assessed toxicity and other relevant data for OP pesticides that assessed inhalation occupational exposure limits (OELs) and to support the development of a risk assessment strategy for OPs in general. Specifically, the value of relative power analysis and the predictability of inhalation by acute toxicity measurements and repeated oral no-observed effect level (NOELs) was assessed. Suggested OELs are based on the prevention of inhibition of AChE in red blood cells (RBCs) and are obtained using a weight-of-evidence approach to risk assessment. Observed effect level (OEL) values between 0.002 and 2 mg/m3, in most cases, were lower than the current allowable exposure levels or threshold limit values. Available data indicated that experimental data for most evaluated OPs were limited; most OPs were equally potent RBC AChE inhibitors in different species of mammals; Repeated exposure study on NOEL of variable duration were generally equivalent and no particular group on the basis of the structure of OPs is always more powerful than the other. In addition, relative power analyzes have limited utility in the risk assessment of OPs. The data also indicated that there was no equivalent of relative power relationships between exposure time (acute versus repeated) or route of exposure (oral versus inhalation). Therefore, consideration of all studies of varying duration and route of exposure is often desirable in the development of an OEL, especially when data are limited. Either no acute measurements or repeated exposures are predictive of OEL based on the weight of evidence. These deviations from the common OP mechanism of action along the duration of exposure and the inhibition of the AChE pathway were probably due to the lack of synchrony between the time of the dose effectiveness of the target tissue and experimental observation of the equivalent response. Therefore, a complete interpretation of all toxicity data in the context of toxicokinetics, toxicodynamics and exposure for each individual based on the evidences information was desirable when the LMTs derive inhalation. 17
Mason (2000) investigated accidental exposures to OPs and plasma cholinesterase and erythrocyte AChE activities in both pesticides-related workers and non- pesticides-relatedworkers. Wide inter-individual variations were reported in baseline enzyme activities of unexposed workers. It was necessary for accurate interpretation of differences in enzymes level of exposed group and control group. The plasma enzyme activity showed an exponential pattern of recovery with a half-life of around 12 days, so recovery was essentially complete after about 50 days. Half-life of recovery was consistent with the reported de novo synthesis rate of plasma cholinesterase. The mean recovery of erythrocyte AChE activity appeared linear over time, attaining unexposed activity after about eighty two days, which was somewhat shorter than the life-span of erythrocytes. It was indicated that pre-exposure baseline levels be established in an individual for a minimum period of 60 days without exposure.
Singh et al. (2000) had described techniques based on the amplification of mycobacterial DNA sequences by polymerase chain reaction (PCR), introduced in many laboratories as a rapid, sensitive and specific promising alternative detection of M. tuberculosis in clinical specimens. New objectives had exploited for the diagnostic PCR, namely devRresponse regulators selected chromosomal fragments rRNA, genes encoding the 65 kDa heat shock protein, 38 kDa protein antigen, DNA gene and insertion sequences, such as IS6110, IS990 and IS1081 were all examples of various objectives that were considered for PCR-based approaches.
Niemann et al. (2000) found that the early and reliable detection of pathogenic mycobacteria in clinical specimens was important in controlling the limitation of human TB. Currently, a tedious set of tests (microbiological, biochemical, etc.) that require more than several days or weeks is commonly used to identify clinical isolates of mycobacteria.
Lacassie et al. (2001a) described a fast, specific and sensitive method for the determination of 29 OP pesticides in blood and serum; the method involves a rapid procedure for solid phase extraction by gas chromatography coupled with selective mass screening. The ionization was by electron impact and the unique mode of acquisition of ion detection of three specific ions followed by the analyte. Recoveries were satisfactory extraction and varied between 40 and 108% in blood and serum. Detection limits ranged from 5 to 25 ng/mL and the limit of quantitation (LOQ) 18 ranged from 10 to 50 ng/mL in blood and serum. An excellent linearity of these quantification limits was observed at 1000 ng/mL. Intra- as well as inter-test accuracy was satisfactory for most analyzed pesticides.
Pitarch et al. (2001) described two methods for the simultaneous determination of multi-residues of OP and organochlorine pesticides in the urine and serum of human samples. The first method was based on simple liquid-liquid microextraction assisted by dichloromethane and the second method involves solid phase extraction with C18 cartridge. The final analysis was carried out using the two capillary gas chromatography methods coupled with nitrogen-phosphorus detector (NPD) and the electron capture detector (ECD). In all procedures, the limits of detection (LOD) were in the low ng/ml level. The solid phase extraction method was applied to real world samples eventually. NPD or ECD was used for quantification purposes and the identification of mass spectrometry (SM) peaks was used.
Tarbah et al. (2001) developed a fast, simple and sensitive method for the determination of OP pesticides using gas chromatography with nitrogen-phosphorus detection (GC-NPD) and the impact of electrons in mass spectrometry, selected ions (GC-MS/SIM). This method was based on one-step selective extraction from twenty different OP pesticides in whole blood, serum, urine samples and certain foods, such as soft drinks, baby foods and instant soups suspected of contamination. The residues were extracted with 1 mL of toluene from an aliquot of 0.7 mL of whole blood sample, serum or urine. An amount of 1 μL of supernatant (toluene phase) was directly injected and analyzed by GC-NPD and GC-MS. Prescribed validation of the method was performed using the slant of human serum. The human plasma recovery ranged from 133% (dialiphos) to 50% (dimethoate).
Frias et al. (2001) developed and validated a reliable, sensitive and selective method for monitoring pesticide residues having endocrine disrupting effects in human serum. The analysis procedure consisted of three steps: extracting with organic solvent serum, cleaning the organic extracts by acid treatment with H2SO4, and eluting the cleaned extracts by gas chromatography and liquid chromatography with end- analysis by electron capture (GC ECD) and tandem mass spectrometry (MS- MS). For both chromatographic methods, performance parameters, such as accuracy, linearity, sensitivity, and recovery were studied. The method developed was applied to the determination of target compounds in serum samples of women living in the 19 agricultural areas of Almeria, Spain. The presented method of operating the (MS-MS) advantage to determine the endocrine disrupters in the matrices and the comparison of MS-MSs and the results of complex ECDs were also made.
Abu-Qare and Abou-Donia (2001) developed a method for the separation and quantification of malathion (O, O-dimethyl-S- (1,2-carbetoxietil) phosphorodithioate) insecticide, its metabolite malaoxon (O, O-dimethyl (3-phenoxyphenyl) metilsester) (3-(2,2 dichloroethenyl)-2,2-dimethylcyclopropane), two of its metabolites, phenoxybenzyl alcohol and m-phenoxybenzoic acid, N, N-diethyl-m-toluamide (DEET) insect repellent, and m-toluamide and m-toluic metabolites in rat plasma and urine. The compounds were separated using a 45 to 99% acetonitrile gradient in water (pH 3.5) at a flow rate between 0.5 and 2 mL/min over a period of 15 min. Retention times ranged from 7.4 to 12.3 min. The detection limits ranged from 20 to 100 ng/mL, while the quantification limits were 50-150 ng/ml. The mean recovery rate of five plasma probe samples was 80.1 ± 4.2, 75.2 ± 4.6, 84.5 ± 4.0, 84.3 ± 3.4, 82.8 ± 3.9, 83.9 ± 5.5, 82.2 ± 6.0, 83.1 ± 4.3 and 78.8 ± 3.9 urine, 76.4 ± 4.9, 82 ± 4 , 5, 82.5 ± 3.9, 81.4 ± 4.0, 83.9 ± 4.3, 81.5 ± 5.0 and 84.5 ± 3.8 for malathion, malaoxon, DEET, M-toluamide, m-toluic, permethrin, alcohol, m-phenoxybenzyl and m-phenoxy- benzoic acid, respectively. The method was reproducible and linear in a range between 100 and 1000 ng/mL. This method was applied to analyze chemicals and metabolites prior to combine dermal administration in rats.
The criteria for differentiation of M. tuberculosis and M. bovis used by Rivero et al. (2001) were colonial morphology, nitrate reduction, niacin test and sensitivity or resistance to pyrazinamide. They reported deviations from standard models in all previous trials, making it virtually impossible to differentiate between M. bovis, M. tuberculosis and M. africanum. The high degree of variability in the phenotypic characteristics has become important to develop reliable techniques to distinguish between the members of M. tuberculosis and M. bovis.
Yassin et al. (2002) evaluated the symptoms of knowledge, attitudes, practices and toxicity associated with pesticide use and exposure among 189 agricultural workers in the Gaza Strip, Egypt; the study subjects completed a questionnaire on knowledge, attitudes, and practices for the use of pesticides and associated symptoms of toxicity. The studied agricultural workers had high levels of knowledge about the health impact of pesticides (97.9%). Moderate levels of knowledge have been recorded high 20 toxic symptoms associated with pesticides. Most agricultural workers were aware of the protective measures to be used when applying pesticides; however, no one took precautions unless they knew measures. The burning sensation in the eyes/face was the most common symptom (64.3%). The prevalence of self-reported symptoms of toxicity depended on mixing and use of high concentrations of pesticides. The highest percentage of self-reported toxicity symptoms was found among agricultural workers returning to spray the fields within one hour after applying pesticides. Farmworkers in the Gaza Strip, Egypt, used a lot of pesticides. Despite their knowledge of the negative impact on the health of pesticides, the use of protective measures was poor. Most, it has had self-reported symptoms of toxicity, especially younger workers. It would be useful to minimize the use of pesticides and to encourage alternative measures. Prevention and intervention programs on the use of measures to protect and monitor the health of agricultural workers should be implemented.
Barr and Needham (2002) reviewed synthetic pesticides used since the beginning of the 20th century. In the United States only, more than 800 active ingredients of pesticides in about 21,000 different commercial products are formulated. Although many benefits to public health have been achieved through the use of pesticides, their potential negative impact on the environment and public health is important. For the evaluation of risk studies, exposure assessment is an integral component, which unfortunately has often been weak or missing. Over the past decades, researchers have proposed to fill these gaps in missing data by monitoring biomarkers related to specific exposures and analytical methods for biological monitoring of pesticide exposure. Critical evaluation of the existing methodology and explore areas where more research is needed.
Wesseling et al. (2002) studied carbamate intoxication and its association with chronic neurobehavioural dysfunction but no epidemiological data on the long-term consequences of carbamate intoxication exists. The neurobehavioral performance of 81 banana workers was assessed who on an average 27 months earlier had received medical care that did not require hospitalization for mild occupational poisoning by OP or carbamate pesticides. Performances were compared to 130 banana workers who never sought medical assistance for poisoning by pesticides. Work performance of poisoned subjects was inferior than controls on psychomotor skills and visual motor skills, language and disease function, with significant differences for coding skills in 21 the Digit-Syrhboltest and two tests for neuropsychiatric symptoms. Deficits, including a marked increase in neuropsychiatric symptoms occurred in subjects poisoned by OPs, but small deficits were also observed in performance in poisoned carbamate subjects. The results of previously poisoned subjects who had contact with cholinesterase inhibitors in the three months prior to the test were particularly poor. Mild intoxication in workers was consistent with previous findings of persistent damage to the central nervous system by OP poisoning. The possibility of persistent neurobehavioral effects associated with poisoning by methyl carbamate insecticide was ruled out. Workers with a history of intoxication may be more sensitive to neurobehavioral effects with subsequent exposures.
Curl et al. (2002) examined exposure to OP pesticides in 218 households of agricultural workers in agricultural communities in Washington State, USA, to investigate the pathway of exposure to pesticides and to establish exposure reference levels for a community intervention project. Household dust samples (n = 156) as well as dust samples collected from vehicle (n = 190) used by farm workers to commute to work were collected. Urine samples from farm workers (n = 213) and small children (n = 211) were obtained from each household. Powder samples were analyzed for six pesticides and urine samples were analyzed for five dialkyl phosphate (DAP) metabolites. Azinfosmethyl was detected at significantly higher concentrations (P < 0.0001) than the other geometric pesticides and azinphos-methyl concentrations were 0.53 mg/g in domestic dust and 0.75 mg/g in vehicle dust. Concentrations of dimethyl DAP metabolite were higher than concentrations of DAP metabolites in urine in children and adults (P < 0.0001). Concentrations of dimethyl geometric DAP were 0.13 mmo/ L in adult urine and 0.09 mmol/L in children's urine. The mean geometric concentrations of adjusted creatinine dimethyl DAP was 0.09 mmol/g in adult urine and 0.14 pmol/g in urine in children. Azinfosmethyl concentrations in house dust and vehicle dust in the same house were significantly correlated (r2 = 0.41, P < 0.0001). Levels of Dimethyl DAP in the urine of children and adults of the same family were also significantly associated (r2 = 0.18, P < 0.0001), and this association remained when the values were adjusted to creatinine. Route of exposure contributed to the dwelling house to the pollution of pesticides in agricultural households where there were small children. 22
Mokrousov et al. (2002) used MAS-PCR (multiplex allele specific polymerase chain reaction) to detect the mutation of isoniazid in the second base of codon 315 of the kat G gene. Mutations in the kat G 315 gene reported on the basis of the presence and absence of a wild-type amplified allele of this codon fragment. They suggested that MAS-PCR can be used for the detection of drug resistance in areas of high prevalence of multidrug resistant strains.
Jyotsna et al. (2003) analyzed a total of 85 subjects (spray operators of pesticides) exposed to different types of pesticides including OP insecticides for 3 to 10 years and compared to 75 controls and reported a significant decrease in serum cholinesterase; the haematological parameters, such as Hb, Ht and RBC in the exposed group were also observed and compared to the control.
Farahat et al. (2003) identified neurobehavioural deficits in workers exposed to OP pesticides in their occupation of application of pesticides to cotton crops in the Menoufiya Estates in Egypt. In their study, 52 male occupationally exposed workers with 50 controls of unexposed males that were similar in age, socioeconomic status, and years of schooling (> 12 years) were compared. All participants completed a questionnaire (personal assessment, professional and medical records) clinical, general and neurological examination, battery of neuro-behavioural tests (including verbal abstraction tests, problem solving, attention, memory and speed visual motor), personality assessment and serological tests for serum AChE. After controlling for confounding age and education, exposed participants showed significantly lower performance than controls in six neuro-behavioural tests (Similarities, Digit Symbol, Trail Part A and B, Cancellation of Letters, Numbers, and Visual Retention Benton). Longer working hours with pesticides were associated with lower performance in most neuro-behavioural tests after adjustment for multiple comparisons. Although serum AChE was significantly lower in the exposed participants than in the controls, it was not significantly correlated with neurobehavioral performance or neurological impairment. Occupational exposure to OP pesticides has been associated with deficits in a wide range of neuro-behavioural functions as previously, possibly due to increased exposure in this population. Moderate chronic exposure to OP can not only affect the vasomotor speed visual but also verbal abstraction, attention and memory previously reported. 23
Soogarun et al. (2003) reported a study on serum cholinesterase of vegetable producers exposed to pesticidal risks in a rural area of Thailand. Seventy subjects (35 vegetable growers and 35 controls) were studied. The mean blood cholinesterase (17.7 ± 7.0 U/ml) level in vegetable producers was significantly lower than in the control group (24.7 ± 12.4 U/ml) (P = 0.01). Jaga and Dharmani (2003) examined the importance of exposure to OP pesticides in public health in the United States. A review of the situation in the United States serves to further highlight the seriousness of the health problems associated with OP pesticides in developing countries. OP pesticides are a group of chemicals that are used primarily in agriculture. OPs inhibit cholinesterase activity ChE-eritrocitos- cholinergic OP toxicity characteristics of enzymes (ChE), (RBC) and the resulting ChE serum. A 50% reduction in serum ChE reference activity is an indication of acute OP toxicity. ChB activity of RBC, which is less rapidly depressed than serum ChE activity, is a measure of chronic exposure to OPs. Exposures to OPs is classified into two categories: occupational and environmental. Occupational exposures occur in agricultural workers (including migrant agricultural workers), industrial workers, pest control exterminators and other workers. Non-occupational exposure affects a large part of the general population in the United States. Residential exposures of the use of OP pesticides exterminator in residents of the home, as well as food and accidental exposure. Other environmental exposures occur in public places and areas close to farms, and exposures can also occur from the use of OP-based chemical weapons or terrorism.
Yassin (2003) studied the biological parameters of OP sprays in the Gaza Strip, Egypt, and four OP sprays seventy commonly dedicated to spraying methamidophos, chlorpyrifos and dimethoate were evaluated. The reference group was represented by thirty people selected from the general population on the basis of never having been exposed to pesticides. Exposure to different OPs significantly decreased serum cholinesterase activity in spray operators (mean = 3891 ± 178 3226 ± 152 IU/L, difference = 17.1%,P= 0.011).
Ramesh and Ravi (2003) developed a novel and sensitive method for the determination of endosulfan residues in human blood by negative ionization chromatography using ionization mass spectrometry (GC-MS/CI) in selective ion- monitoring mode (SIM). Residue extraction was performed using whole blood 24 without separating the serum using 60% sulfuric acid at 10°C, followed by separation with hexane + acetone at a ratio of 9: 1 (in volume). Quantification was carried out for endosulfan as the sum of its isomers, such as α-endosulfan, β-endosulfan and endosulfan monitoring SIM. For this purpose, mass fragment ions were monitored in the SIM mode, including α-endosulfan: 99, 242, 270, 406; endosulfan sulfate: 97, 353, 386; endosulfandiol: 95, 169, 214, 313 and β endosulfan: 99, 242, 270 and 406. The concentration range of 1.0 to 100 μg/mL was used for recovery experiments. Recovery of total blood samples varied endosulfan 112-98% and relative standard deviation (RSD), was 1.49 to 40 2.68%. The sensitivity of the method for the quantification of total endosulfan was found to be 0.1 μg/mL. The applicability of the presented method was tested for the determination of endosulfan residues in 106 human blood samples collected from a population living in Padre Village, Kerala, India. The results revealed that none of the blood samples were positive for the presence of endoslufan isomers (alfaendosulfan 4 + endosulfan beta-endosulfan sulfate).
Bhatia et al. (2003) reported that TB remains a major health problem in most developing countries and its incidence is increasing even in many developed countries. This resurgence was attributed to human immune deficiency virus (HIV) and TB was declared a global health emergency by the world health organization. The diagnosis of TB mainly depends on the results of clinical and radiological initial suspicion with subsequent confirmation by bacteriological sputum smears and culture. Lack of sensitivity in smear examination and specificity for radiological findings prolonged rotation of cultured M. tuberculosis and bacillary diagnostic created difficulties. Extra pulmonary TB needed to be explored by immunodiagnostic utility of TB as a practical and cost-effective test. In addition to the clinical information for the final diagnosis many commercial tests are available in the market for the diagnosis of TB. Most of these tests are based on the detection of IgG, IgA and IgM against the specific antigen or a mixture of mycobacterial antigens. Immunoassays indigenous systems explored mycobacterial ES-31 excretory antigens for immunodiagnosis of secretory TB. Often there is a lack of coherent elevation in all three classes of Ig to active infection, so it is more important to determine the ideal antibody test isotypes for a reliable diagnosis of TB and to reduce costs of unnecessary investigations to the patients.. 25
Clarke et al. (2003) conducted a study in the Boland Health District (BHD) in the Cape Wine Country County in South Africa where there is high incidence and prevalence of TB. A survey of 211 farms in the District during the 1998 study indicated that 65% (n = 9042) of all workers temporarily employed on these farms were infected. Temporary agricultural workers live in communities inside or outside the boundaries of BHD from where they are transported every day to work. To estimate the spot prevalence of tubercle sputum smear among temporary agricultural workers in the BHD and determine whether temporary agricultural workers diagnosed with TB had access to treatment of TB, a cross-sectional survey of adult seasonal agricultural workers in the four study farms in BHD revealed TB (self-reported) cases and six new cases of smear-positive TB. The overall point prevalence was 10 cases of TB in the cohort of seasonal agricultural workers, resulting in a one time prevalence of 2809 cases per 100,000 temporary agricultural workers (95% CI: 1090- 4527). Excluding the four self-reported cases of TB in the calculation, the point prevalence of new cases of smear-positive TB was six and the prevalence of 1,685 cases (95% CI: 468 -2909). Of the four self-reported cases of TB, their drug supply was depleted, while the remaining three indicated that they needed treatment at home. Prabhakar et al. (2004) investigated molecular detection of presence of M. bovis in patients with hup BMDR-TB by gene amplification to differentiate strains of M. tuberculosis and M. bovis. PCR amplicons 645 and 618 bp was generated by N and S primer in M. tuberculosis and M. bovis, respectively. The C-terminal PCR amplicons of M. tuberculosis and M. bovis were determined to be 318 and 291 bp, respectively. The differences in the C-terminal portion of the gene were confirmed by restriction fragment length polymorphism analysis and sequencing. Sequence analysis indicated that in M. bovis there was a deletion of 27 bp in frame after codon 128 in the C- terminal part of the hupB gene. One hundred and four mycobacterial strains and eleven non mycobacterial species were analyzed for hupB gene sequences. Of the mycobacterial strains, 62 belonged to the MTB complex and 42 were non-MTB complex strains and species. Neither the hupB gene-specific primers (N and S) nor the C-terminal primers (M and S) amplify DNA from any other mycobacteria. The assay was suitable for distinguishing members of the MTB complex from other mycobacterial species, as well as for differentiating between members of the MTB complex, namely, M. tuberculosis and M. bovis. 26
Ejigu and Mekonnen (2005) assessed the health status, attitude and level of awareness of safe pesticide handling practices of farm workers engaged in the application of pesticides on agricultural farms. Farm workers had respiratory symptoms of cough, phlegm and wheezing. Systolic and diastolic blood pressures did not show abnormalities. Elevated level of liver function test liver abnormality. Respiratory symptoms in the workers revealed that cough phlegm and wheezing at Ayehu farm were significantly (P < 0.05) higher than the controls. Alkaline phosphatase (ALP) at Birr Farm in the sprayers and mechanics were significantly higher than the controls (P < 0.05). The ALP value in the sprayers, glutamate pyruvate transaminase (GPT) in the assessors and glutamate oxaloacetate transaminase (GOT) in the sprayers and mechanics at Ayehu were significantly higher than the controls (P < 0.05). Out of a total of 82 farm workers, 35.7% at Birr and 75% at Ayehu farm described that they were not formally instructed about safe pesticide handling methods. The farm worker’s health was affected by the unwise use of pesticides. The level of awareness and attitude on safe pesticide handling practices was low.
Alarcon et al. (2005) had shown that exposure to pesticides in schools was associated with disease among employees and students, albeit rarely. Pesticide exposure rates in schools had shown to be higher in school staff personnel than in children because staff was more likely to handle pesticides. Exposure to pesticides can cause coughing, shortness of breath, nausea, vomiting, and headache and eye irritation.
Tsoukali et al. (2005) used solid-phase headspace microspace (SPME) and optimized for the determination of OP pesticides in four common biological samples. The choice of the type of SPME fiber and the added salt content, preheating and extraction time, duration of desorption, extraction temperature: several parameters controlling the SPME were studied. Capillary gas chromatography analysis with nitrogen phosphorus detection (GC-NPD) facilitates the sensitive and selective detection of SPO: malathion, parathion, parathion-methyl and diazinon. Fenitrothion was used as an internal standard. The method has been applied for the determination of pesticides in human biological samples: whole blood, blood plasma, urine, cerebrospinal fluid, liver and kidneys. Detection limits ranged from 2-55 ng/mL depending on the pesticide and the type of sample. The methodology overcomes the limitations and obstacles of conventional methods, such as the use of organic solvents, emulsion 27 formation and cumbersome procedures. The proposed protocol was considered an interesting alternative to be used in routine toxicological analyses.
Chakravorty and Tyagi (2005) reported a new, robust, reproducible methodology and treatment of universal versatile samples for highly sensitive smear microscopy, culturing in solid and liquid media and PCR without inhibition that is appropriate for laboratory diagnosis of both pulmonary and extra pulmonary TB. Method explored the chaotropic properties of guanidinium hydrochloride for the treatment of samples and involves incubation of the sample with USP solution, concentration of bacilli by centrifugation and use of the treated sample for smear microscopy, culture and PCR. The detection limit for acid-smear bacilli is doped with about 300 bacilli per ml of sample. The samples treated with the solution were fully compatible with the solid and liquid culture media. It could be isolated by amplifiable PCR quality of mycobacterial DNA from all types of clinical specimens treated with a USP solution. The method has been widely validated with pulmonary and extra-pulmonary samples. In addition, the method was compatible with microscopic examination of smears, culture and PCR other than M. tuberculosis bacilli. The method provided microscopy, culture and nucleic acid amplification technologies with a single sample processing platform and is most likely the only method described to date. It was useful for laboratory diagnosis of TB and other classical mycobacterial diseases and modern methods.
Yang et al. (2005) described MAS-PCR as a rapid and cost-effective method for the detection of resistant genetic mutations related to first-line drugs for TB detection . It used 174 clinical TB isolates and correlated band profiles between MAS-PCR and sequencing was 99.4% and the sensitivity-based method of sensitivity and specificity cultures was 81.1% and 97, isoniazid 5%, 93.0% and 98.9% for rifampicin and 54.5% and 68.0% for ethambutol. Molecular method based on PCR or for the differentiation of M. bovis and M. tuberculosis in patients with MDR-TB was developed. The first molecular characterization of M. bovis was carried out in 1997 in the Netherlands. Antonio et al. (2006) reported that the effects of acute pesticide poisoning are well known for the most commonly used pesticides but simply no data are available? on health effects after prolonged exposure to low doses. Key outstanding issues include the effect of moderate exposure in the absence of poisoning. The increased use of pesticides other than OPs makes it even more difficult to find associations. A cohort 28 of 106 intensive agricultural workers were evaluated twice during a seasonal spray for changes in serum biochemistry, i.e., enzymes reflected cytotoxicity (AST and ALT) and other biochemical parameters as markers of nephrotoxicity (BUN, creatinine) and lipid profile (cholesterol and triglycerides). Several criteria for estimating exposure to pesticides were used, the most significant depression of the top of serum cholinesterase 25% of baseline exposure to the maximum. It was revealed that an association of exposure to pesticides with changes in AST (increased activity), LDH and amino oxidase (decreased activity), as well as changes in serum creatinine and phosphorus (Lower and upper levels, respectively). Results provided support for a very slight deterioration of liver function, but in general these findings are consistent with no clinically significant hepatotoxicity. Interestingly, it was found that R- paraoxonase-1 allele was an independent predictor of higher levels of AST and amino oxidase, so that could play a supportive role in a single susceptibility marker to effects on pesticide-induced health. Biomarkers can be used to detect the early biochemical effects of pesticides before adverse health effects occur.
Dulaurent et al. (2006) introduced an analytical method for the simultaneous determination of dialkyl phosphatase known as urinary indicators of exposure to OP pesticides, using liquid tandem chromatography mass spectrometry (LC-MS/MS). DAP selected for this study were dimethiotriphosphate, dietiltiofosfato, dimethyl phosphate dimethyldithiophosphate, dietillditiofosfato; an internal standard dibutyl phosphate was also used. The procedure involved liquid-liquid extraction and detection using mass spectrometric detector modes with multiple negative ion reaction followed by two ionic changes per compound. Limits of quantification (LOQ) mg/L and coefficients of variation were calculated below 20%. The analytical method developed was successfully validated by investigating urine samples from a small cohort of exposed volunteers and at least one of the six DAPs was found in each urine sample. The results demonstrated the feasibility of a method/MS-MS LC to evaluate the overall exposure of the population to some commonly used OP pesticides. Early et al. (2006) reporting on agricultural workers in North Carolina, USA, discovered that 46 percent of agricultural workers who lived in very overcrowded and unhealthy conditions increased their exposure to environmental toxins and infectious diseases. 29
Leilanie and Delprado (2007) in their cross-sectional study determined association between hematological indices related to exposure to pesticides in cut flower producers in the Philippines. One hundred and two randomly selected cut flower producers, including children, were examined to supplement physical and laboratory health and responded to a questionnaire on work practices and diseases. The results showed that the diseases due to pesticides (P = 0.005) correlated with abnormal VGM. Significant associations were also found for hemoglobin, hematocrit, RBC, WBC and platelet count.
Olga et al. (2007) reported that various pesticides, including OPs induce oxidative stress due to the generation of radicals and free alterations in antioxidant defense mechanisms. In their study, a cohort of 81 intensive agricultural workers (pesticide spray operators) was evaluated twice during a spray season for changes in antioxidant erythrocyte enzymes. AChE was used as a reference biological marker. Sprayers had lower levels of superoxide dismutase (SOD) and glutathione reductase (GR) compared to controls, regardless of age, body mass index (BMI), smoking or alcohol consumption. A positive correlation between SOD and AChE during the period of high exposure was observed. Those with a decline of 15% higher AChE SOD activities presented and catalase lower during the same period. Glutathione peroxidase (GPx) and glucose 6-phosphate dehydrogenase (G6PD) were not affected in the exposed population. Paraoxonase polymorphism (PON1) influenced CAT and erythrocytes GR, as subjects with the R allele had lower CAT and higher GR levels. If the enzymatic activities decreased found related to adverse health effects to the chronic toxicity of pesticides (in which oxidative damage plays a pathophysiological role, such as cancer or neurodegenerative diseases) was an attractive assumption that deserves further investigation.
Inoue et al. (2007) reported a fast and simple method for measuring 10 OP pesticides in the serum of patients with acute liquid chromatographic mass spectrometry (LC- MS) poisoning. The OP insecticides were selected for this study included acephate, methidathion, dichlorvos, fenthion, diazinon, phenthoate, malathion, fenitrothion and cyanophos. An aliquot of the biological sample was injected after deproteinization with acetonitrile on a C18 column using 10 mM ammonium methanol formate as eluent. The extraction of the satisfactory coatings was obtained in the range between 60.0 and 108.1% of serum. LOD and LOQ serum were between 0.125 and 1 μg/ -mL 30 and between 0.25 and 1.25 g -/ -mL, respectively. Following the successful application of this method in a real case of acute intoxication, it was concluded that because of its precision and simplicity, it could be useful for the determination of OP pesticides and could also be very useful for clinical toxicology and forensic toxicology.
Labenia et al. (2007) found that cholinesterase activity was commonly applied in bio- monitoring exposure to OPs and carbamates and in the diagnosis of poisoning of anticholinesterase compounds. One of the groups at risk of pesticide poisoning was workers involved in the production of these chemicals. Study was to evaluate the effect of pesticides on cholinesterase activity in erythrocytes and serum workers who were professionally exposed to these chemicals. The subjects were 63 workers of a pesticide plant. Blood samples were taken prior to use and after 3 months of field work. Cholinesterase levels were determined in erythrocytes (EChE) using the modified method (Ellman method) and serum cholinesterase (SCHE) by assay substrate butyryl thio choline. Mean levels were 48 ± 11 IU/g Hb and 37 ± 17 IU/g Hb (matched t-test, mean = -29, 95% CI = -43 to 14), P < 0.001). The average dry level was 9569 ± 2496 IU/l and 7970 ± 2067 IU/l (matched t-test, mean = 1.599, 95% CI = 1140-2058, P < 0.001). There was a significant increase in ALT (P < 0.001) and a decrease in serum albumin (P < 0.001). Among pesticide workers, it appears that routine assessment of the levels of workers employed in these occupations and cholinesterase pesticide managers should be mandatory.
Arcury and Quandt (2007) evaluted that agricultural workers are six times more likely to develop TB compared to other workers, and had reported positive TB rates between 17% and 50% in the United States. Lack of access to health services, including the detection of TB and pharmaceuticals, can make the diagnosis inappropriate. It is estimated that three-quarters of agricultural workers lacked all sources of health insurance. Khan et al. (2008) working in Swabi District, Pakistan, reported an enormous amount of irrational use of pesticides in the country. The authors determined that the residues plasma frequency of pesticides was greater than the acceptable daily intake (ADI); they studied its correlation with biochemical markers for the assessment of adverse health effects on snuff producers. In their study, 109 adult males trained by 55 farmers exposed to snuff pesticides and 54 controls were included. The pesticide 31 residues in the blood were analyzed by HPLC and GC-NPD. Plasma butyrylcholinesterase (BChE) was analyzed by the Ellman method. Biochemical markers, including serum calcium, phosphorus, BUN, creatinine, bilirubin and liver enzymes were measured in Selectra-E auto-analyzer. Snuff producers had several pesticide residues above the ADI in their blood, consisting of 35 (63%) of methomyl; 31 (56%) of thiodicarb; 34 (62%) cypermethrin; 27 (49%) imidacloprid; 18 (32%) of methamidophos and 15 (27%) of endosulfan. ChE activity decreased significantly among farmers exposed to pesticides compared to controls (P < 0.001). Biochemical markers of plasma, including ALT, AST, CK, LDH and phosphate increased significantly in farmers exposed to pesticides as compared to the control group (P < 0.001). Total pesticide residues showed a significant positive correlation with AST (r = 0.42), LDH (r = 0.47), ALT (r = 0.20) and phosphorus (r = 0.51). Excessive exposure to pesticides caused cytotoxic changes in biochemical liver and kidney markers that were positively correlated with pesticide residues. Therefore, these biomarkers could be more useful to monitor the activity of BChE and adverse effects of pesticides on the health of agricultural workers.
Joshaghani et al. (2007) determined that cholinesterase activity is commonly applied in exposure to OP and carbamates and in the diagnosis of anticholinesterase poisoning compounds. One of the groups at risk of pesticide poisoning was workers involved in the production of these chemicals. To evaluate the effect of pesticides on cholinesterase activity in erythrocytes and serum in workers who were professionally exposed to these chemicals. The subjects were 63 workers of a pesticide plant. Blood samples were taken prior to use and after three months of field work. Cholinesterase levels were determined in erythrocytes (EChE) using the Ellman method and serum cholinesterase (SCHE) by assay substrate butyrylthiocholine. Mean levels were 48 ± 11 IU/g Hb and 37 ± 17 IU/g Hb in (matched t-test, mean = -29, 95% CI = -43 to 14 , P < 0.001). The average dry level was 9569 ± 2496 IU/L and 7970 ± 2067 IU/L in (matched t-test, mean = 1.599, 95% CI = 1140-2058, P < 0.001). There was a significant increase in ALT (P < 0.001) and a decrease in serum albumin (P < 0.001). The significant decline among pesticide workers, it appears that routine assessment of the levels of workers employed in these occupations and cholinesterase pesticide managers should be mandatory. 32
Gamlin et al. (2007) evaluated the effect of exposure to OPs and carbamates on levels of AChE in young Mexican migrant workers and younger siblings. Blood samples from 160 children aged 14 years were collected during harvest (exposure) and 62 children in their communities of origin 6-9 months after harvest (basic). Cholinesterase samples corrected for hemoglobin and temperature were analyzed. Fifty percent of the children had depression scores ranging from -40% to 190% of their baseline levels. Thirty-three percent of children had depression scores of at least 15% while 86% of children were anemic. Weigel et al. (2007) reported that malnutrition increases the likelihood of latent TB infection turning into an active infection. Their 2007 study in Texas and New Mexico, USA, revealed that 82% of agricultural workers were food insecure and 49% of those were hungry. Workers who were often exposed to pesticides were at increased risk of bovine TB.
Kedia and Palis (2008) examined acute and chronic effects of pesticide exposure on rice farmers in the Philippines. They collected data on 50 farmers in 2002 and 2003 using a semi-structured questionnaire to obtain demographic information, various aspects of life in agriculture, types and extent of farming, use of pesticides, media exposure and experiences of self-reported acute and chronic diseases. Participants in the study had been farming for 20 years and applying an average of four to six pesticides about three times a year. The most common acute health problems reported by farmers were fatigue (52.0%), dizziness (50.0%) and bodily pain (32.0%). Farmers reported 43 different types of chronic health-related symptoms which were categorized as neurological (98.0% observed by farmers), skin (90.0%), systemic (88.0%), respiratory (88. 0%), ophthalmic (82.0%), gastrointestinal/renal (80.0%) and cardiovascular (56.0%). Chronic health conditions were significantly lower for farmers who sold pesticide empty containers (B = 3.479, P = 0.01), for those with higher annual incomes (B = -0.000, P = 0.01) and those with vocational training compared to the single primary school (B = 6.101, P= 0.02).
Kasiotis et al. (2008) determined fenthion residues in human serum samples by developing a simple and effective analytical method. Microextraction (HS-SPME) polyacrylate solid phase fiber was used for the treatment of the sample, which requires a small amount of serum (1 mL) without tedious pretreatment. For the determination of residues in fenthion serum samples, gas chromatography 33 spectrometry (GC-MS) was used and herringbone coatings two levels for 6 repetitions ranged between 79 and 104 %. Limits of detection (LOD) and limits of quantitation (LQ) were calculated as 1.51 and 4.54 ng/ml, respectively. Two metabolites of fenthion, fentrosulfóxido and fenoxon were also identified.
Lebailly et al. (2008) identified the parameters associated with exposure to pesticides of French farmers in agricultural fields . Field volunteers were monitored for one day using isoproturonon herbicide and/or barley during winters of 2001 and 2002 under normal working conditions. The whole body method was used to evaluate potential dermal exposure with blankets and cotton gloves. The loading and application tasks were assessed separately with 12 different areas of the body (hands, arms, forearms, legs, chest, back and thighs) application separately. Daily potent isoproturon exposure varied from 2.0 to 567.8 mg (median 57.8 mg) in 47 farmers. Exposure during blending tasks accounted for 13.9 to 98.1% of total exposure (median 74.8% in May). For the feed mixture, hands and forearms were the most polluted areas of the body accounting for an average of 64 and 14%, respectively. For application, hands were also the most contaminated part of the body, representing an average of 57%, and thighs, forearms and chest or back were in the same range as other 3-10%. There was no correlation between dermal exposure potential and spray area or duration of spraying or farm size. However, a significant relationship between exposure and the type of spray equipment with a rear mounted sprayer leading to a level higher than the exposure of the trailer sprayers was observed. The technical problems, especially disconnection of the spray nozzles, and the number of loading tasks or application of the mixture was also significantly associated with higher levels of exposure. Ofukwu et al. (2008) reported that M. bovis infection is definitely a work hazard for agricultural workers who can acquire inhalation of infected bovine spray cough. While M. bovis is a major cause of pulmonary TB in cattle, it also is the leading cause of extra pulmonary TB in humans in cases where cow's milk is usually consumed fresh and unpasteurized.
Soomro et al. (2008) reported that pesticides are the main chemical contaminants in the agricultural environment and a hazard to the exposed population. These compounds are absorbed by inhalation, ingestion and skin contact. Bioavailability in individuals can lead to a variety of definitive and systemic metabolic dysfunctions, and even disease. Thus, the enormous use of pesticides has promoted community 34 spraying. Spray operators of pesticides (n = 140) and controls (n = 110) had highly significant effects by analytical sero-cholinesterase level (P < 0.001). Several range classification for monocrotophos and carbaryl were similar, but different from endosulfan and cypermethrin, which conceptualized the effects on levels of cholinesterase. GC-MS detection of residual concentrations in blood serum samples from sprayer workers; calculated for endosulfan, monocrotophos, cypermethrin and carbaryl were 0.009, 0.005, 0.05 and 0.08 mg/kg body weight, respectively.
Rastogi et al. (2008) assessed impact on health of spray operators using OP insecticides including 34 male children in Malihabad, North India. BuChE blood levels and whole blood were compared between spray operators after spraying pesticides and to those determined in a reference group (n = 18). BuChE plasma had significantly decreased among workers. The results indicated a significant decrease in mean hemoglobin, hematocrit and platelet count; however, a significantly higher number of leukocytes was also observed in the pesticides-exposed group (atomizers) than in the control group (P < 0.05).
Khan et al. (2008) reported that snuff is an important cash crop in Pakistan and an enormous amount of irrational pesticides are used to control insect growth on it. Residues plasma frequency of pesticides greater than the (ADI) and its correlation with biochemical markers for the assessment of adverse health effects on snuff producers in Sawabi District of Pakistan was determined. Of the total 35 (63%) of methomyl; 31 (56%) of thiodicarb; 34 (62%) cypermethrin; 27 (49%) imidacloprid; 18 (32%) of methamidophos and 15 (27%) of endosulfan. BChE activity decreased significantly in farmers exposed to pesticides compared to controls (P < 0.001). Biochemical markers of plasma, including ALT, AST, CK, LDH and phosphate increased significantly in farmers exposed to pesticides as compared to the control group (P < 0.001). Total pesticide residues showed a significant positive correlation with AST (r = 0.42), LDH (r = 0.47), ALT (r = 0.20) and phosphorus (r = 0.51). Excessive exposure to pesticides caused cytotoxic changes in biochemical liver and kidney markers that were positively correlated with pesticide residues. Therefore, these biomarkers could be used to monitor the activity of BChE to monitor the adverse effects of pesticides on the health of agricultural workers.
Mosudi et al. (2008) analyzed blood serum of cocoa producers as well as their domestic water sources for pesticide residues in selected cocoa growing 35 communities in southwestern Nigeria. In their study, farmers were grouped into five exposure periods according to their years of participation in the application of insecticides, i.e., < 5 years, 5-9 years, 10-14 years, 15-19 years and > 20 years. Residue analysis revealed that 42 of the 76 farmers had residues of diazinon, endosulfan, propoxur and lindane in their blood; and 47.6% of these farmers belonged to the exposure period of more than 20 years. Approximately 34% of the farmers had diazinon with an average concentration of 0.067 mg kg/L, 29% had endosulfan (average = 0.033 mg/ kg), 23% had propoxur (average = 0.095 mg /kg) in blood. Residues of lindane, endosulfan and propoxur in all exposure duration categories were found to be well below the no-observed-adverse-effect level (NOAEL), while residues of diazinon detected in the blood serum of farmers in all exposure duration categories exceeded 0.02 mg /kg. The study also revealed that sources of drinking water were contaminated with dazinón and propoxur in some of the farmer’s towns; the insecticide concentrations exceeded the acceptable daily intake (ADI). Cocoa producers in southwestern Nigeria were professionally exposed due to the application of insecticides to control mirides on their cocoa plantations and at times the exposure is dangerous for farmers and their communities.
Singh et al. (2008) compared conventional methods with molecular methods for the detection of pulmonary TB in vitro. Sputum specimens were collected from 150 patients with pulmonary TB in clinical diagnosis and 50 control (non-TB) patients. These 200 samples were subjected to microscopic smear, egg-based culture medium and the mycobacteriophage test. Compared to the PCR method, the sensitivity of MGIT-960 was 90%, 76.7% for FASTPlaque, 73.3% for the L-J culture method and 60% for microscopic smear assay method.
Cunningham et al. (2008) reported that workers emigrating from central American countries with the highest incidence of TB in southern Mexico and poor areas were potentially likely to have more TB epidemics and documented TB in the US in immigrants from central America who worked in the agriculture business.
Bhoopendra and Dogra (2009) developed a simple and rapid method for estimating certain OP insecticides in the serum of occupationally exposed individuals. The compounds are extracted with a mixture of acetone and diethyl ether (1: 1 v/v) in an acidic medium and the extraction residue is analyzed by gas chromatography with a nitrogen fluorescent substance detection method. Linearity was acceptable at 36 concentrations of 0.25 to 4.0 mg/mL. The percentile recovery method for six different OP insecticides was 86.3% for phorate, 78.3% for dimethoate, 82.3% for malathion, 79.4% for chlorpyrifos, 80.2% for diazinon and 68.5% % for the ethion level pg/mL. Serum samples from nine workers who had been professionally exposed to malathion were found to have low levels of the pesticide in all samples that were analyzed. In Nigeria, Ani et al. (2009) compared molecular diagnosis of TB with conventional methods. They collected sputum samples from 101 HIV-positive patients and compared the detection of TB by microscopic examination of Ziehl-Neelsen (ZN) smears, L-J culture and PCR method. In target PCR specific for M. tuberculosis "6110" having multiple copies of the same and absent in other mycobacteria. The sensitivity and specificity of PCR were 85% and 74%, respectively, compared to 23% and 100% for Zn microscopy. One of the molecular methods for the detection of MDR-TB is the specific PCR multiple allele (MAS-PCR), which allows simultaneous detection of resistance to the first line and second line drugs.
Hayat et al. (2010) analyzed blood samples from field workers involved in pesticide application on 3 different farms in Vehari District of Punjab, Pakistan, for the evaluation of pesticide residues. Twenty seven workers were selected for this field study (including 3 controls) in the age range of16-50 years and had practically applied pesticides for 1 to 9 years. In this study, blood samples for the determination of 383 pesticides were analyzed but only chlorpyrifos and pídicártico (concentration of 0.009 mg/L and 0.001 mg/L, respectively) were detected.
Araoud et al. (2010) developed a method for estimating carbamate residues and OP pesticides that were widely used in Tunisia. Liquid-liquid extraction followed by tandem mass spectrometry (LC/MS/MS) chromatography in elctrospray mode for the identification and quantification of the compounds was used. To monitor the MS/MS change for each compound, multiple reactions monitoring (MRM) acquisition mode was used. In three different levels of fortification, average recoveries for most pesticides ranged from 65% to 106%, with the exception of methamidophos. Depending on the analyte, the linearity with a correlation coefficient of 0.995 to 0.999 varied from 5 to 50 g/L. The calculated LOD and LQ were 2 μg/μL and 5 g/L, respectively.
Lee et al. (2010) provided an overview of the mortality and prevalence of related diseases among agricultural workers in south Korea and estimated the age- 37 standardized mortality rates and prevalence of chronic diseases and compared them with those of other populations. Agricultural workers had a significantly higher mortality rate due to cancer, TB, chronic respiratory diseases, liver diseases, suicide, automobile and non-automobile accidents. Compared to other populations, farmers had higher prevalence of arthritis and intervertebral disc disorders. It was also revealed that a number of other related diseases were more prevalent among farmers, such as musculoskeletal diseases, poisoning by pesticides, infections and respiratory and neurological diseases. Farmers showed a different pattern of mortality and disease prevalence compared to other populations. Although lifestyle factors remain important contributors to these deaths and diseases, the study suggested that the profession is also an important factor. The authors recommended development of intensive programs, such as surveillance systems to identify and prevent work-related diseases among agricultural workers in South Korea.
Muddasir et al. (2010) assessed the burden of chronic exposure to pesticides by estimating pesticide residue levels in random human serum samples from Dal Lake villagers, India. Exposure of humans to hazardous chemicals in the field occurs directly and indirectly through the consumption of contaminated food or by inhalation or skin contact. From 2008 to 2010, a total of 600 blood samples were taken from three population groups designated PG-1, PG-2 (study groups) and PG-3 (control group) and analyzed for seven commonly used pesticides, namely butachlor, -HCH, chlorpyrifos, hexaconazole, endosulfan 1 endosulfan 2 and dichlorovos. The detection and quantification of pesticide residues was carried out using gas chromatography-gas mass spectrometer equipped with an electron capture detector Ni. Of the seven pesticides tested, only chlorpyrifos was detected in all three population groups. The mean concentration of chlorpyrifos in the study groups (PG-1 and PG-2) was 0.5194 ± 0.6456 ng/uL and the control group (PG-3) was 0.0008 ± 0.0009 ng/uL. Analysis of variance revealed a significant difference in the mean concentration of chlorpyrifos between PG-1, PG-2 and PG-3. Tuckey’s HSD (Honestly Significant Difference) test showed that PG-1 and PG-2 did not differ significantly (P value: 0.300) in the mean concentration, whereas PG-3 differed significantly from PG-1 and PG-2 (P value: 0.000 ). This indicated that the average level of pesticide concentration was higher in the Dal lake population than in the control group. The results suggest that 38 chronic low-dose exposure to pesticides directly or indirectly may be a significant presence of residual levels of pesticides in human blood serum.
Skrzypczak et al. (2011) provided a cost-effective way for human bio-monitoring to identify and quantify exposure to chemicals, including those that have deleterious effects on human organs and reported particularly high risk of exposure to hazardous chemicals was associated with the pesticides used in agriculture, specifically the most widely used OP pesticides in the world. There is strong evidence that chronic exposure to these compounds had adverse health effects.
Singh et al. (2011) designed a study to evaluate genotoxicity, AChE activity, liver and kidney toxicity among workers exposed to the pesticide. DNA comet tail was used to measure DNA damage, while the activity of AChE and other biochemical parameters, such as nephrotoxicity and hepatotoxicity (AST, ALT and ALP) used as biomarkers for toxicity due to exposure to pesticides. Workers were continuously exposed to the mixture of pirimifosmethyl, chlorpyrifos, malathion and temephos at regular intervals depending on use and activity. Comet assay using exposed laboratory lymphocytes showed a significantly higher TD (60.43% versus 31.86%, P < 0.001) and a TM value (14.48_mvs, 6.42_m, P < 0.001) among exposed workers compared to controls. The activity of AChE in erythrocytes decreased (3.45 KAU/L compared to 9.55 KAU/L in controls, P < 0.001) and was associated with the duration of exposure to pesticides used by workers . The enzyme levels for liver and kidney functions were also found to be significantly different in pesticidal operators than in control subjects (P < 0.001). Exposure to pirimiphos-methyl blend, chlorpyrifos, temephos and malathion can induce DNA damage, decrease AChE activity, hepatotoxicity and nephrotoxicity. The authors recommended biomonitoring of these biomarkers, as well as education and training of workers for the application of pesticides for their potential hazards.
Richard et al. (2011) estimated the prevalence and correlated latent infection of TB among residents of an agricultural community migrating to San Quintin, Baja California, Mexico. Residents completed a questionnaire and underwent blood tests for ITL using the QuantiFERON_-TB Gold In-Tube (QFT) test. Among the 133 participants, 39.8% (95% CI: 31.5 to 48.7%) tested QFT positive. The high prevalence of LTBI in this community emphasized the need for education on TB and LTBI treatment for its residents. Large QFT-positivity between unpasteurized milk 39 consumption may indicate infection by M. bovis, previously reported among Mexican migrants living in border towns of the United States.
Adama (2012) interviewed workers including occupationally exposed agricultural workers and crop protection agents in the Sahel region of Burkina Faso, West Africa, to assess the adverse health effects of insecticides, such as changes in haematological and biochemical parameters. The author discovered prevalence of hepatic and renal dysfunction to be quite high among pesticide applicators, particularly plant protection agents. The prevalence of biochemical alterations appeared to be correlated with the frequency of insecticidal use. However, no significant differences between haematological parameters in agricultural workers and crop protection agents were found. Haematological parameters of all pesticide applicators were normal; however, a vast majority (85%) of pesticides applicators having symptoms of exposure to insecticides clearly indicated that the use of insecticides in agriculture in Burkina Faso threatens human health.
Emam et al. (2012) evaluated the effect of pesticides on haematological parameters in agricultural workers in southwestern Iran. Fifty four men that were exposed to pesticides and 54 healthy male subjects (control) were enrolled in the study and Hb, HCT, MCV, MCH, MCHC and ESR, the number of cells (red blood cells, white blood cells and platelets) and coagulation factors between the pesticides-exposed and control groups were measured. Agricultural workers between 17 and 65 years of age were (35±8). All haematological parameters that were tested were within the normal range. The values of Hb, Hct, RBC, platelets and PT in the exposed group were higher than in control group. Haematological indices were measured in the group of cases, but these were not significant compared to normal (p P > 0.005). RBC, Hb, platelets and PT are useful clues as warning signs for the rapid diagnosis of pesticide poisoning.
Latif et al. (2012) assessed pesticide residues in human blood samples collected from volunteers in the Districts of Hyderabad and Mirpurkhas, Pakistan. Volunteers in the two Districts were divided into four groups based on their duration of exposure to pesticides. Group A-5 was at 9 years of age, Group B-10 at 14 years, Group C-15 was at 19 and 20-year-old. Out of a total of 188 volunteers, 145 volunteers (77.1%) were agro-industrial while 43 volunteers (32.9%) were non-agricultural subjects. Chlorpyrifos residues, endosulfan, 1,1,1-trichloro (p-chlorophenyl) ethane (p, p'- 40
DDT) and parathion, 2,2-bis were detected in numerous samples. The predominant pesticides in the blood samples of the two District volunteers were chlorpyrifos (with a mean concentration of 0.37 mg/kg in group D Mirpurkhas) and endosulfan (with the highest mean concentration of 0.30 mg/kg in group D of Hyderabad). The amount of pesticide residues detected in some blood samples from the agro professionals was alarming.
Awad et al. (2013) reported from Egypt that significant increase in pesticide use has raised concerns about the adverse effects on human health and the environment. Effects of exposure to pesticides on liver function and levels of AChE in serum and red blood cells of hundred men involved in agricultural work between the ages of 20 and 60 years with an average age of 37.11 ± 9.3. was estimated while 100 men in the same age range and socioeconomic status were observed as a control group to compare levels of alanine aminotransferase (ALT), aspirin aminotransferase (AST), bilirubin, alkaline phosphatase (ALP ), total protein, malaise and acher. The results indicated that AST, ALT and ALP were highly significant (P < 0.05) in workers exposed to pesticides compared to control. There was also a significant decrease (P < 0.01) in male farm workers compared to controls. Depending on the number of applications of pesticides, there was a positive correlation between total AST, ALP, and direct bilirubin and the number of pesticide applications. Egypt's agricultural villagers were demanding more attention to increase the literacy rate of farmers and increase their knowledge about health.
Dhalla and Sharma (2013) assessed the level of irregularities in cholinesterase caused by pesticides used by spray operators to their exposure periods, age and body mass index (BMI) of atomizers in rural District Punjabi of Bathinda in East Punjab, India. They found a positive correlation between the activity of schemes and years of exposure period and a significant reduction of SchE activity in a younger population. Again, a positive correlation between BMI and dry inhibition was observed. Mahmood et al. (2013) evaluated a rare liver condition (peliosishepatis) in combination with chronic pulmonary TB. The results revealed a prevalence of 7.47% of bovine TB. Frequency analysis revealed that the prevalence of the disease did not significantly differ with age, sex and stage of lactation. The autopsy revealed several resizable tubercles in the lungs. The trachea and the bronchial tree were largely covered with sparkling yellow spongy purulent exudates. Microscopically, the lungs 41 showed small and large nodules with caseado-shaped center and caseous lamellar arrangement that was surrounded by giant cells, epithelioid macrophages, plasma cells, and lymphocytes and fibrous in colored pulmonary tissues Ziehl masses - Neelsen expressed bacilli in necrotic centers. The infectious agent (M. bovis) was confirmed by PCR peliosis hepatis; histopathological findings are useful for the differential diagnosis of acute chronic bovine TB information.
Costa et al. (2013) analyzed the paraoxonase 1 (PON1) as a genetic determinant of susceptibility to OP toxicity. Human PON1 showed two polymorphisms in the coding region (Q192R and L55M) and several polymorphisms in the promoter and the 3'- UTR regions. The Q192R polymorphism imparts differential catalytic activity toward some OP substrates, while the polymorphism at position -108 (C/T) was the major contributor of differences in the levels of PON1 expression. It was found that PON1 was an important determinant of OP toxicity. Administration of exogenous PON1 to rats or mice protects them from the toxicity of specific OPs. PON1 knockout mice display a high sensitivity to the toxicity of diazoxon and chlorpyrifos oxon, but not of paraoxon. In vitro catalytic efficiencies of purified PON 192 alloforms for hydrolysis of specific oxon substrates accurately predict the degree of in vivo protection afforded by each isoform. Evidences were slowly emerging and low PON1 susceptibility increased due to OP toxicity in humans. Low PON1 activity contributed to the developmental toxicity and neurotoxicity of OPs.
Aradhna and Singh (2014) estimated the effects of spraying pesticides on hematological parameters in pesticide sprayers in Kasganj Uttar Pradesh, India, by using 50 pesticidal spray subjects and 26 non-exposed (to pesticides) control subjects. They analyzed hematological parameters, including RBC, WBC, hematocrit, and DLC platelets.. No significant differences in platelets, granulocytes and lymphocytes were found, whereas RBC, WBC, and hematocrit values were significantly different (P < 0.05) in the pesticide sprayers compared to the control group, indicating that hematological parameters could be used to detect the chronic effects of exposure to pesticides while mixing.
Neupane et al. (2014) described the use of pesticides by farmers and compared possible symptoms of acute poisoning and levels of erythrocyte AChE in vegetable producers to control blood donors in the Nepal group. They used 90 farmers that were exposed to pesticides and 90 unexposed control group blood donors. Data were 42 collected through questionnaires, observation and blood tests. Chi-square, logistic regression and Student's t-test were used for data analysis to describe the use of pesticides and compare symptoms and AChE levels between the two groups. Most of the pesticides used were WHO class II, classified as moderately hazardous. The average number of personal protective equipment used by farmers was 2.22 (95% CI: 1.89 - 2.54). Among five hygiene practices, farmers followed a hygiene practice of 3.63 (95% CI: 3.40- 3.86) on average. Farmers reported more symptoms of pesticide poisoning in the last month than controls, with an average of 5.47 (95% CI: 4.70 - 6.25) compared to 2.02 (CI 95%: 1.63 - 2.40) (P < 0.05). The average AChE adjusted to hemoglobin (Q) was significantly lower among exposed farmers than controls, 28.92 (95% CI: 28.28 - 29.56) U/g vs. 30.05 (CI 95%: 29.51- 30.60) U/g, (P = 0.01). The risk that a farmer had a lower level of Q was about 3 times more (OR = 2.95, 95% CI: 1.16 - 7.51) than in controls.
Tilak and Sravanthi (2014) studied neurotransmitter enzymes, such as the effects of acetyl- and changes in butylcholinesterase in humans exposed to OP pesticides during agricultural spraying practices in areas of Nuziveedu Krishna District, INDIA. The reported changes were important because it was found that more than 45% of AChE and 36% butylcholesterol (BChE) decreased in the exposed group compared to the unexposed control group. The first absorption by people resulting from chronic toxicity as the production of oxygen free radicals, being metabolically heterotrophic, results in altered homeostasis leading to an oxidative stress culminating antioxidants continuously maintaining due to imbalance.
Jennifer et al. (2014) identified occupational and personal characteristics associated with the inhibition of butyrylcholinesterase (BuChE) in agricultural pesticide managers in Washington State, USA, during the OP/CB dew season for a period of six years (2006-2011). In relation to the initial pre-season levels, the mean decrease in BuChE activity during OP/CB season spraying throughout the study period was 3.77% (P < 0.001). A greater BuChE inhibition was observed between manipulators who reported using OP/multiple OC (β = -2.70, P = 0.045), OP/OC mixed or loaded (β = -3.97, P = (Β = -3.4, P = 0.014), or did not use chemical resistant boots (β = - 16.6, P < 0.001) which included a higher number of registered pesticide managers for a longer period of time. The use of several OP/OCs and mixing/loading activities were important risk factors, and the use of chemical resistant boots and cabinets for 43
PPE storage were protective factors. It highlighted the logical interventions to reduce exposure, such as the implementation of engineering measures for mixing/loading activities, requirements for appropriate footwear and the regular use of storage cabinets of personal protective equipment.
Sukonthaman et al. (2015) described agriculture as the main occupation in Thailand and the factors associated with pesticides used and the level of plasma cholinesterase and other emerging issues among agricultural workers in Baan Na Yao, Thailand. Qualitative interviews and quantitative questionnaires were used to gather information from agricultural workers (mainly cassava and rice crops) directly exposed to pesticides within two months simultaneously. Qualitative participants were selected through reasoned sampling and total quantitative survey. The quantitative data were analyzed statistically using several logistic regression models. The qualitative data were transcribed and analyzed thematically. For the qualitative study, 15 participants were interviewed and 300 out of a total of 323 (92.88%) participants were given questionnaires, of which 175 were men and 125 women. The prevalence of abnormal levels of plasma cholinesterase was 92.28% (risk ratio 7.72% 49.33% and 42.95% unsafe). Participants with inappropriate spraying behavior had a significant association with plasma cholinesterase level (95% CI = 1.399 - 14.858), but other factors had no association. Although they had reasonably high knowledge but attitude always had a bad behavior. PPE also realized, but insufficiently and misinterpreted the symptoms caused by the use of OPs as the allergy. Occupational health education, modification of PPE and regular medical monitoring were required to address the concerns of agricultural workers and determine if there was any progression in the long term.
Cotton et al. (2015) observed Australian farmers and their workers were exposed to a wide variety of pesticides. OPs is a widely used class of pesticides used for breeding practices (naphthalophos for dip sheep, spraying and drainage), crop production for pest control (dimethoate) and public health. Acute poisoning with this type of insecticides is reported in agricultural workers and children worldwide, due to the inhibition of AChE. Chronic exposures are less known. Regular monitoring of erythrocyte AchE allows farmers to identify potential exposure to OP insecticides and take measures to reduce exposure and improve health and safety practices. Evaluated and improve the integration of AChE surveillance into routine clinical care and 44 provide agricultural and non-farm people with a link between their AChE activity and its domestic chemical and agrochemical use. Basic data on demographics, health conditions and behaviors, Kessler 10 (K10), use of personal protective chemicals were collected. Also, basic anthropometric measurements including height, weight, hip circumference and girth, body fat analysis and biochemical analysis of total fasting serum cholesterol, triglycerides, low-density cholesterol (LDL), high density cholesterol (HDL) and blood sugar were taken. Analysis of the activity of AChE was carried out using a finger prick test repeated in all participants every three weeks for up to three times over a ten week period. Participants received a comprehensive evaluation and advice on their activity after each reading and a detailed summary to all participants was provided at the end of the study. The data were analyzed using repeated measurements in a general linear model. An evidence base and recommendations for the integration of Australian rural health clinical surveillance leading to research that further quantifies exposure to pesticides both on-farm and at home, stressing the importance of maintaining a safe environment for work and family farming communities was provided.
Adad et al. (2015) reported that agricultural workers in Brazil are often exposed to pesticides which are products belonging to a specific chemical group that affects the health of agricultural workers and most are recognized as genotoxic and carcinogenic. Exposure of workers in Piaui, Brazil, assessed these hazardous chemicals and cytogenetic changes using micronuclei, hematologic and lipid oral dosage parameters, butyrylcholinesterase (BChE) activity and genetic polymorphisms of the enzymes involved in pesticide metabolism, PON1, and the DNA repair system. Two groups of agricultural workers exposed to different types of pesticides were compared to unexposed control groups. There was a significant increase in the frequency of micronuclei, kariorrexis, caryolysis and binuclear cells in exposed groups (n = 100) compared to controls (n = 100). No differences in haematological parameters, lipid profile and BChE activity were detected. No significant differences in DNA damage and nuclear fragmentation were observed when specific genotypes of metabolism and DNA repair were studied in the exposed groups.
Chadha and Jagota (2015) reported TB as the world's foremost cause of death from a single infectious agent and annually there are about 3 million deaths from TB all over the world with about 15% of these occurring in India alone. The brunt of the disease 45 is borne by those in the age group of 15-59 years. Approximately 6.7% of all deaths and 18.5% of deaths in the above age group, in the developing world are attributable to TB. An estimated one-third of the world population is infected by M. tuberculosis, with 95% of TB cases occurring in developing countries. Among more than 1000 million people in India today, every second adult is infected with the tuberculous mycobacteria and each year more than 2 million people develop active TB. India alone accounts for nearly one third of the global burden of this disease.
Aroonvilairat et al. (2015) found that many Thai orchid farmers used excessive amounts of pesticides without protective equipment and evaluated the immunological, haematological and biochemical states of these farmers. They had 64 orchid farmers and 60 controls subjects in their study. Plasma cholinesterase activity, percentage and absolute number of B lymphocytes (CD19+) were significantly lower in the farmer group (3966.32 ± 1165.48 U/L, 11.61 ± 4.09% and 312.26 164.83 ± cells / mm 3, respectively) as compared to the control group (5048.85 ± 1139.40 U/L, 14.32 ± 4.23%, 420.34 ± 195.18 cells/mm 3, respectively). A statistically significant level of serum IgE in orchid farmers (0.031 ± 0.011 mg/DLV, 0.018 ± 0.007 mg/dL) was observed, however, levels of IgG, IgA and IgM were not observed. The level of lysozyme in serum, the proliferative responses of lymphocytes to mitogens, haematological parameters and renal function test were not significantly different between the two groups. Profiles of liver function showed significantly lower levels of serum albumin and protein in farmers as compared to control.
Garcia-Garcia et al. (2016) studied the associations between occupational exposure to pesticides and various negative health outcomes assessed in individuals at two points in the same growing season with use of different pesticides. Clinical symptoms signs of physical, hematological and clinical chemistry examinations in 189 intensive agricultural workers and 91 healthy subjects (control) were measured at to assess the potential effects of exposure to pesticides. Greenhouse workers showed an increased risk of ocular and cutaneous signs compared to controls during the period of high exposure to pesticides (OR 4.80 and 2.87, respectively); however, no differences in clinical symptoms were observed. An increased risk of changes was found in the ECG (OR: 3.35) and a modified spirometry (OR: 5.02) in the low exposure period. Erythrocyte AChE decreased significantly in greenhouse workers compared to controls in both periods. 46
Damalas and Koutroubas (2016) reported that synthetic pesticides are widely used in agriculture to control pests and prevent harmful losses in crop yields or product damage. Due to the high biological activity and, in some cases, long-term persistence in the environment, pesticides can cause adverse effects on human health and the environment. Farmers were regularly exposed to high levels of pesticides, usually much higher than those of consumers. The exposure of farmers occurs mainly during the preparation and implementation of solutions for the spraying of pesticides and cleaning of spraying equipment. Aditionally, farmers who mix, load and spray pesticides can be exposed to these chemicals from spills and splashes, or direct contact with the spray as a result of defective, missing or even drifting protective equipment. However, farmers may also be exposed to pesticides, even when they are engaged in activities that are not directly related to the use of pesticides. Farmers who perform manual labor in areas treated with pesticides may face significant exposure by direct spraying, diversion of neighboring fields or contact with pesticide residues in the crop or soil. This type of exposure is often underestimated. Dermal and inhaled vestibules are generally the most common routes of exposure of farmers to pesticides. Dermal exposure during normal handling of pesticides occurs in areas of the body not covered by protective clothing, such as face and hands. Exposure of farmers to pesticides can be reduced through less use of pesticides and by proper use of appropriate type of personal protective equipment at all stages of pesticide management.
Jamal et al. (2016) explored the effect of exposure to pesticides on the reproductive health and hepatic function of women involved in agriculture-related jobs. Fifty women were enrolled by age and socioeconomic status as a control group to compare hormone levels (estradiol, progesterone and follicle stimulating hormone), liver enzymes ALT and AST. Fifty six percent of the studied women were illiterate and 48% represented involvement in agricultural work. Women who helped on farms showed a higher incidence of adverse pregnancy outcomes, such as abortions and stillbirths than non-participants. There was a significant increase in levels of estradiol and progesterone in agricultural workers. Although there was an increase in serum hepatic enzymes but (AST and ALT) there was a significant decrease in the level of follicle stimulating hormone in women involved in agricultural activities. 47
Participation of women in agricultural activities likely to be exposed to pesticides jeopardizes their reproductive health and liver functions.
In India, Deshpande and Srivastava (2016) reported the validated methods for the analysis of post-mortem samples, especially tissues by the HPLC. It was validated a simple reversed-phase high-performance liquid chromatography ultraviolet method for the simultaneous determination of carbamate (propoxur), OPs (malathion, quinalfos, profenofos, and chlorpyrifos), and organochlorine (endosulfan) pesticides in post-mortem tissue and blood samples. The pesticides incorporated in the method were those commonly encountered in suicidal or homicidal poisonings in India. Validations were proved by the applicability of matrix-matched and by calibration screening of the pesticides in post-mortem samples. The working range of all the pesticides showed good linearity with correlation coefficients (r) values ranging from 0.9996 to 0.9999. The limits of detection for all pesticides ranged from 0.37 to 0.70 μg/g in tissue while it varied from 0.14 to 0.35 μg/mL in blood. The limit of quantification ranged from 1.16 to 2.50 μg/g in tissue and from 0.44 - 1.50 μg/mL in blood. The developed method can be effectively used for confirmation and quantification of the pesticides belonging to diverse groups which required different time consuming and costly analytical techniques for screening.
48
MATERIALS AND METHODS
In current research, health conditions of pesticidal spray workers (n = 200) exposed to pesticides in comparison with healthy individuals (n = 100), not exposed to pesticides, were evaluated by performing different hematological (complete blood count) and biochemical (liver ALT and AST) tests levels of AChE (an enzyme involved in the termination of synaptic/nerve impulse transmission) in serum along with detection of traces of OP pesticides, i.e., profenophos, chlorpyrifos, dichlorovos, malathion in serum of pesticidal spray workers. Moreover, as exposure to pesticides may lead to weak immune system, infection of TB was also checked in spray workers by using molecular test in which histone-like protein (hupB) gene of mycobacteria was targeted. The spray workers included in current research had worked in the field for quite a long duration of time, i.e., more than ten years. The target group of spray workers was selected from District Gujranwala who had worked in the field and had used various formulations of OP insecticides. As exposure to pesticides may lead to hematological abnormalities, liver dysfunction, neurological disorders and immunological problems with high rate of infections, current research was carried out to investigate these aspects as well along with possible environmental risk factors.
3.1. Study design
The base line study was conducted in District Gujranwala of Pakistan (31◦-32–32◦ 33’ latitudes N and 73◦ 11–74◦ 28 longitudes E); the District is situated in Punjab Province of Pakistan (Figure 3.1) (Annexure I). The study was conducted during January 2014 to June 2016 involving two hundred spray workers and one hundred healthy individuals that served as control. District Gujranwala was selected for the specific study because it is one of the major crops cultivation areas of Punjab. The majority of spray workers of this area had very little or no formal education and was generally not aware of the adverse effects of pesticides on their health. Considering this scenario, there was a dire need to conduct the present study and generate information in order to help reduce the risks of exposure to pesticides and the resulting adverse effects of pesticides on the health of agricultural spray workers.
49
Figure 3.1: Map of District Gujranwala (Punjab, Pakistan) showing location of the study area (www.googlemap.com).
The study area covered approximately 850 square kilometers out of a total of 3198 square kilometers area occupied by the Gujranwala District. It included 115 villages out of a total of 800 villages in the District.
3.2. Questionnaire-based survey 50
Information concerning all the study individuals (pesticidal spray workers as well as healthy individuals) was collected using a structurally designed questionnaire (Annexure II) containing the educational level of workers, use of personal protective equipment and clothing during preparation of pesticides for spraying, safety practices adopted by workers during spraying, and health symptoms that workers experienced after spraying activity, such as nausea, vomiting, headache, skin irritation, eye irritation, coughing, backache, weight loss, loss of appetite and sleeping disorder.
3.3. Sample size
In current research, a total of two hundred spray worker (n = 200) routinely exposed to pesticides were included while one hundred (n = 100) inhabitants of the same area(s) that were not exposed to pesticides (healthy individuals) were also included as control. The age of spray workers ranged between 20-60 years and these workers comprised of one hundred and fifty (n = 150) males and fifty (n = 50) females; . while one hundred (n = 100) control subjects were fifty males (n = 50) and fifty females (n = 50).
3.4. Sample collection and processing
Prior to blood sampling, written consent from all study subjects was taken. All the phlebotomy procedures were carried out under WMA (2008). Fresh blood sample (5 ml) from each study individual was drawn by well-trained medical technologist into vacutainer tubes from each of the spray worker as well as control subject. . About 2.5 ml blood was dispensed into EDTA coated vacutainer for hematological analysis. The remaining blood sample was put into serum separation tube containing gel in order to separate serum from the blood. Then serum samples were obtained by centrifugation at room temperature by using the centrifuge (Rotina 46 Hettich, Japan) at 4000 rpm for 3 minutes and later serum samples were stored at -700C for subsequent analysis including liver function test, serum AChE level and to detect the traces of pesticides in blood serum.
3.5. Hematological analysis
Whole blood count analysis was performed for both spray workers (n = 200) and control individuals (n = 100) for samples collected in EDTA containing tubes by using (Sysmex XE-2100 Automated Hematology Blood Analyzer, Lincolnshire Illinois, USA) blood analyzer system. The major blood parameters studied were white 51 blood cells count (WBC), red blood cells count (RBC), hemoglobin (Hb), haematocrit (HCT), lymphocyte count (LYM), mean corpuscular hemoglobin concentration (MCHC), neutrophils count (NEUT) and monocytes count (MON). Hematological indices among pesticidal spray workers and control group was calculated.
3.6. Serological analysis
Serum enzyme ALT (UL-1) was estimated by using kit (ALT Cat. No: AL2360) and aspartate amino transferase (AST) (UL1) (AST Cat. No: AS2359) manual method in randox semi auto biochemistry analyzer (RX altona, USA).
3.6.1. Alanine aminotransferase (ALT)
Method principle
Alanine aminotransferase catalyzes the transfer of the amino group from alanine to 2 oxoglutarate, forming pyruvate and glutamate. The catalytic concentration is determined from the rate of decrease of NADH, measured at 340 nm, by means of the lactate dehydrogenase (LDH) coupled reaction. Equation (i) below shows the assay based on activity of ALT enzymes reaction. Equation (i) [Alanine + 2 – Oxoglutarate Pyruvate + GlutamatePyruvate + NADH+H +Lactate + NAD+] Assay Wavelength: 340 nm Optical Path: 1 cm Temperature: 37ºC Measurement: against air (decreasing absorbance) Warm the reagents and the cuvette to the desired temperature. Temperature must be kept constant (± 0.5ºC) for the duration of the test.
3.6.1.1. Procedure
Bring the working reagents and the photometer to 37ºC. Pipette into a cuvette: ALT Working Reagent Standard (S) or sample 1.0mL Mix thoroughly and incubate the cuvette for 10 minutes at room temperature or for 5 minutes at 37ºC. Measure the absorbance (A) of the standard and the sample at 500 nm against the blank. The color remains stable for at least 2 hours.
Calculation 52
A Sample X C Standard = C Sample A Standard 340nm: U/l = ∆A/min ×1745 Normal range: 70 – 105 mg/dl. Reference values: Women upto 32 U/l Men upto 37U/l
3.6.2. Aspartate aminotransferase (AST):
Method Principle
Alanine aminotransferase catalyzes the transfer of the amino group from alanine to 2 oxoglutarate, forming pyruvate and glutamate. The catalytic concentration is determined from the rate of decrease of NADH, measured at 340 nm, by means of the lactate dehydrogenase (LDH) coupled reaction. Equation (ii) below shows the assay based on activity of AST enzymes reaction.
Equation (ii) [Alanine + 2 – Oxoglutarate Pyruvate + GlutamatePyruvate + NADH +H+ Lactate + NAD+]
Assay
Wavelength: 340 nm
Temperature: 37ºC
Measurement: against air (decreasing absorbance)
Warm the reagents and the cuvettes to the desired temperatures. Temperature must be kept constant (± 0.5ºC) for the duration of the test.
3.6.2.1. Procedure
Working reagent and the instrument were set to required reaction temperature and then pipetted into a cuvette. Reagent temperature was raised to 37ºC. One mL of working reagent was mixed with 100μL of serum sample and cuvette was inserted into the photometer. Then initial absorbance was recorded after an interval of 1 minute and thereafter for 3 minutes. Difference between the consecutive absorbance was noted. The average absorbance difference per minute (ΔA/min) was calculated.
Calculation 53
340nm: U/l = ∆A/min ×1745
ΔA/min x ε x I x V S = U/L
Normal range, for AST up to 38 U/L.
3.7. Biochemical analysis
3.7.1. Determination of cholinesterase activity
The procedure used for the determination of cholinesterase in serum samples was based on the method described by Ellman et al. (1961). Assay was carried out by using Amplex Red Acetylcholine/ AchE Kit assay.
Principle
Cholinesterase hydrolyses butyrylthiocholine under release of butyric acid and thiocholine. Thiocholine reduces yellow potassium hexacyanoferrate (III) to colorless potassium hexacyanoferrate (II). Decrease of absorbance was measured at 540 nm.
3.7.2. Acetylcholine Assay
Assay of acetylcholine in a total volume of 200 µL per micro plate well was carried out. Acetylcholine standard curve was prepared by diluting the appropriate amount of 100 mM acetylcholine stock solution (Annexure IV). Stock solution was prepared into 1X reaction buffer (Annexure III) to produce acetylcholine concentrations of 0 to 100 µM. 1X reaction buffer (1X) without acetylcholine was used as a negative control. A volume of 100 µL was used for each reaction. It was noted that the acetylcholine concentrations was twofold lower in the final reaction volume. Acetylcholine containing samples were diluted the in 1X reaction buffer. Positive control was prepared by diluting the 20 mM H2O2 (Annexure V) working solution to 10 µM in 1X reaction buffer. One hundred µL of the diluted samples and controls were pipetted into separate wells of a micro plate. Working solution of 400 µM Amplex Red reagent containing 2 U/mL HRP, 0.2 U/mL choline oxidase and 1 U/mL AChE by adding 200 µL of Amplex Red reagent stock solution, 100 µL of the HRP stock solution (Annexure VI), 100 µL of the choline oxidase stock solution (Annexure VII) and 100 µL of the AChE stock solution (Annexure IX) to 9.5 mL of 1X Reaction Buffer was prepared. Reactions were started after adding 100 µL of the Amplex Red reagent/HRP/choline oxidase/AChE working solution to each microplate well containing the samples and controls. Reactions were incubated for 30 minutes 54 and protected from light. Fluorescence was measured in a fluorescence micro plate reader (ELx 800 ELISA reader, BioTek Instruments, Winooski, VT, USA) using excitation in the range of 530–560 nm and emission detection at 540 nm. The results to define acetylcholine concentration by standard curve was calculated by using Microsoft Excel (2010) (Annexure X) and then statistically analyzed by Statistical Package for Social Sciences (SPSS version 21).
3.8. Determination of levels of immunoglobulins
OP insecticides effect on immunological response of spray workers was assessed by analyzing level of immunoglobulin. Immunoglobulin levels were calculated by using ELISA (enzyme linked immunosorbent assay).
Principle
The sandwich ELISA measures the amount of antigen between two layers of antibodies. The antigen to be measured must contain at least two antigens sites capable of binding to antibody.
3.8.1. Protocol
The serum concentration of immunoglobulins was measured using ELISA kit (Cat # MBS 571035, Bio-source Company, San Diego, California, USA). Sandwich ELISA was performed in accordance with the defined modified protocol of Aroonvilairat et al. (2015). Samples were diluted appropriately and the average dilutions for IgA, IgM, and IgE analysis were about 1:150000, 1:50000, 1:2, respectively. Then microtitter plates were coated with antibodies at concentration of 5µg/ml in coating buffers (0.05M bicarbonate buffers, pH 9.6). Microtitter plates were covered with the cover plate and incubated overnight at 4 ºC. Washing of coating solution was carried out by filling the wells with 200 µL 1xPBS (phosphate buffer saline) and 0.05% Tween 20. Washing solution was removed by pipetting with a multichannel micropipette. The remaining drops were dried up by putting the micotitter plate on blotting paper. Remaining protein binding sites were blocked by adding 200 µL of 5% BSA/PBS per well. Plates were again covered with adhesive plastic cover plate and incubated again for 1 to 2 hours at room temperature. Then 100 µL of serum samples were added to each well and incubated again for one hour. Washing was performed by filling each well with 200 µl PBS. Then incubated again for one hour after adding 100 µL secondary antibody and HRP (horse raddish peroxidase). Washing was carried out 55 four times with PBS. Immediately 100µl blocking buffer was added to stop the reaction and washing was performed. Then absorbance was measured at 450 nm on ELISA reader (ELx 800 ELISA reader, BioTek Instruments, Winooski, VT, USA).
3.9. High Performance Liquid Chromatography
HPLC analysis
For HPLC analysis method of Lacassie et al. (2001b) was used with some modifications. HPLC analysis was carried out by following the below given steps.
3.9.1. Preparation of standard of pesticides
Pesticides standards of HPLC (High Performance Liquid Chromatography) grade for profenofos, chlorpyrifos, dichlorovos, malathion, and imidacloprid were obtained from Ali Akbar group of industtries Lahore, Pakistan. Standard solution (1ppm) (Annexure XI) was prepared by mixing the pesticides technical grade standard into mobile phase (acetonitrile, water). Standard and mobile phase were of HPLC grade. All the sample solutions were filtered through 0.22 µm pore size micro filters.
3.9.2. Preparation of the sample (serum samples pretreatment for HPLC)
3.9.2.1. Protein precipitation
Protein precipitation was carried out to remove proteins from serum samples for preventing the adsorption of proteins in the HPLC column. For this, 500 µL of organic solvent (ethanol) was added to 500 µL of the serum sample. Sample solution was mixed well with the precipitant solution and was kept at a cool place for 15 min. Protein was precipitated. Then samples were centrifuged at 1700 rpm for 15 min in centrifuge machine (Rotina 46 Hettich, Japan). Proteins precipitates were settled at the bottom of the eppendorfs. Filtration was performed by using cosmonice syringe filter (pore size 0.22 µm). Syringe plunger was pushed to filter the sample. Then deproteinization was confirmed by taking O.D. at 280 nm () UV visible spectrophotometer (Spectrumlab 752s Shanghai, China). Filtered solution was collected in the collection tube and analyzed by HPLC.
3.9.2.2. Filtration assembly 56
Ultrafiltration was carried out by passing of all samples and mobile phase through filtration assembly apparatus. During filtration microfilters (0.22 µm pore size) were used to clean the samples for HPLC analysis.
3.9.2.3. Sonication
After filtration the next step was sonication. Samples were sonicated at 31°C for 15 minutes. During sonication all types of gas bubbles were removed. Thereafter, HPLC analysis was carried out on L series -HPLC system (Hitachi ) with florisil ODS-C18 column (150 x4.6) with 5 µm pore size and elite chrome (L-2400 ) detector, pump (L- 2100-2130) and autosampler (L-2200).
3.9.3. Optimization of condition for HPLC
Specification of HPLC for analysis of the pesticides in blood serum samples are given below in Table 3.9.3.1. Optimized conditions for various pesticides analyzed by HPLC are given in the Table 3.9.3.2- 3.9.3.6.
Table 3.9.3.1. HPLC conditions for the pesticides analysis in serum
Character Specification
Column Intersil ODS-C18 column
Column 150*4.6*5
Mobile phase Acetonitrile : Water
Pressure 1 mL/min
Injection volume 10 µL
Detector UV visible 57
Table 3.9.3.2.Optimized HPLC conditions for dichlorovos pesticide in blood serum of agricultural workers.
Pesticide name Dichlorovos
group Organophosphate
wavelength 254 nm
Mobile phase acetonitril: Water, 92:8
Flow rate 0.85 mL/min
Retention time 4.2 min
Injection volume 10 µL
% purity 99.9%
.
58
Table 3.9.3.3. Optimized HPLC conditions for prophenophos pesticide in blood serum of agricultural workers.
Pesticide name Prophenophos
Group Organophosphate
wavelength 282 nm
Mobile phase Acetonitrile : Water, 65:35
Flow rate 2mL/min
Retention time 4.1 min
Injection volume 10 µL
% purity 95%
59
Table 3.9.3.4. Optimized HPLC conditions for chlorpyrifos pesticide in blood serum of agricultural workers.
Pesticide name Chlorpyrifos
Group Organophosphate
Wavelength 230 nm
Mobile phase Acetonitril: Water, 70:30
Flow rate 2mL/min
Retention time 12 min
Injection volume 10 µL
% purity 97%
60
Table 3.9.3.5. Optimized HPLC conditions for malathion pesticide in blood serum of agricultural workers.
Pesticide name Malathion
Group Organophosphate
Wavelength 260 nm
Mobile phase Acetonitril: Water, 24:76
Flow rate 2mL/min
Retention time 7.3 min
Injection volume 10 µL
% purity 95%
61
Table 3.9.3.6. Optimized HPLC conditions for imidacloprid pesticide in blood serum of agricultural workers.
Pesticide name Imidacloprid
Group Neonicotinoid
Wavelength 270 nm
Mobile phase Acetonitril: Water, 70: 30
Flow rate 1mL/min
Retention time 11.2 min
Injection volume 10 µL
% purity 99.9%
62
3.9.4. Quantification of pesticides by HPLC
3.9.4.1. Area \Height method
Amount of the pesticides was calculated from the peak area by using Equation (i), (ii) and (iii)
…………………... Equation (i)
……………….. Equation (ii)
……...Equation (iii)
A = Area
H = Height
3.10. Tuberculosis detection in suptum of spray workers
Prevalence of TB among agricultural spray workers (n = 200) and healthy unexposed individuals to pesticides (n = 100) was assessed by molecular method in which HupB gene of mycobacteria was targeted in PCR-based method. The sputum samples were used for the detection of M.tuberculosis and M. bovis. Briefly, to the sputum sample equal volume of autoclaved distilled water (1 ml) was added under aseptic conditions to make suspension. This suspension was stored at -70 0C for subsequent use for the isolation of total genomic DNA for TB detection.
3.10.1. Molecular detection of tuberculosis
The total genomic DNA from sputum samples of pesticide exposed spray workers (n = 200) as well as healthy unexposed individuals to pesticides (n = 100) was isolated by adopting the kit method of GeneAll ( S. Korea). The molecular detection and differentiation of M. tuberculosis and M. bovis was carried out by adopting the procedure of Prabhakar et al. (2004).
63
3.10.2. Genomic DNA isolation
The genomic DNA isolation from samples was carried out by the following procedure of GeneAll Genomic DNA purification kit with some changes. The steps involved in the isolation of genomic DNA are described below: The bacterial cells pellet was obtained by centrifugation of 0.3 ml of sputum suspension sample at 12,000 rpm for 5 minutes. To the pellet, 200 µl TE buffer (1mM EDTA pH 8.0 and 10 mM Tris-Cl pH 8.0) was added and re-suspended and then it was centrifuged at 12,000 rpm for 1 min. The step was repeated until clear cell pellet was obtained. Then, it was centrifuged at 10,000 rpm for 2 min. Supernatant was removed while pellet was saved. To the pellet, 300 μL buffer AL (Cell Lysis Solution) was added and mixed well by vortexing so that the pellet was completely homogenized and disappeared in the buffer. Proteinase K (3 μL) was added and eppendorf tube containing sample was incubated overnight at 55oC. Samples were cooled down to room temperature for 5 minutes. Then 100 μL of buffer PP was added and mixed well by gentle vortexing. Samples were incubated in freezer for 5 minutes and were centrifuged at 1,000 rpm for 2 minutes. Supernatant was removed carefully and transferred to new autoclaved and labelled eppendorf tube. Then 300μl of chilled isopropanol/absolute ethanol was added. Transparent thread like appearance was observed in the tube. The solution was mixed very gently and incubated in freezer for 1 hour. After incubation, the solution was centrifuged at 1,200 rpm for 8 minutes. Supernatant was discarded immediately and the DNA pellet was allowed to dry at 500C for half hour or longer as this time may increase until the DNA pellet was completely dried and all the traces of isopropanol were removed. After drying the DNA pellet, 50-100 μl of injection water was added and gently mixed well for 4-5 minutes. The purified DNA sample was stored at -20oC in freezer for subsequent use.
64
3.10.3. Agarose gel electrophoresis of genomic DNA
The DNA isolation was verified by agarose gel electrophoresis. DNA extract of 6 μL was mixed with 4μL sample loading dye in a parafilm paper. The mixture was then loaded into a sample well of 0.8 % agarose gel and 6µL of DNA ladder having a size range of 100 to 10,000 bp was added between wells of the gel to indicate the DNA fragment size. Gel was run at 100 V for around 45 minutes. The gel was examined and the DNA band was visualized under UV light in transilluminator.
3.10.3.1. Quantification of DNA
Visual comparison by gel electrophoresis as well as the spectroscopic method was adopted to quantify isolated genomic DNA. DNA was loaded on 1% agarose gel and DNA marker was also loaded for comparison quantified under UV-light by comparing the intensity of the band with the marker bands. DNA can also be quantified spectroscopicaly by taking the absorbance at 260 nm using water blank. The quantity of DNA was calculated by the following formula:
Amount of DNA (µg/mL) = 50 X OD X Dilution Factor
OD = Optical density value of DNA sample at 260 nm.
Dilution Factor = Numberof times the sample was diluted.
The purity of the DNA was checked by taking the absorbance at 260 and 280 nm and calculating the value of 260/280 ratio. If the value of this ratio remains above 1.5 then the DNA is good to be proceeded further for molecular analysis.
3.10.4. Preparation of 1% the agarose gel for PCR product analysis
In 250 mL flask, 50 ml TAE buffer and 0.5 g agarose powder were added. Agarose was melted in a microwave oven for 1min at 100°C for several short intervals to avoid boiling of the solution because boiling for long period could boil out the agarose gel from the flask. Thereafter, the solution was allowed to cool down to 50- 55°C, by swirling the flask occasionally and 3 µL ethidium bromide was added to the gel. Combs were placed in the gel mold for creating the wells. Melted agarose solution was poured into the casting tray and left to cool down until it solidified. The combs were pulled out carefully. Gel was placed into the electrophoresis chamber. TAE Buffer was added to about 2-3 mm of buffer over the gel. Power supply was set to 100 voltage for 30 minutes. Leads of gel box were attached to the power supply. 65
Power supply was turned on and working of both ends of gel box was verified. The cathode (black leads) was kept closer to the wells than the anode (red leads). Power supply was turned on and gel was run until the migration of the dye to an appropriate distance. After completion of electrophoresis, power supply was turned off and gel was removed from gel box and placed into transilluminator gel documentation system. After taking the gel picture gel was disposed of properly.
3.10.4.1. Loading of the gel
In each 25 L PCR reaction 6 L of 6X sample loading buffer was added. The order of samples loaded on gel was recorded. Ten L of the DNA ladder was pipetted out and loaded into one well of each row on the gel.
3.10.5. Polymerase chain reaction
PCR amplified products of the M. tuberculosis and M. bovis were determined by using a single set of PCR primers. The primers M and S were used to generate amplicons of sizes 318 and 291 bp which represented M. tuberculosis and M. bovis, respectively.
66
Table 3.10.5.1. Concentration and volume of reagents used for PCR.
PCR chemicals Stock concentration Volume used (μL)
PCR reaction buffer 10X 5
MgCl2 25 mM 3
DNTPs 10 mM 4
Forward primers 10pmol/ μL 1.5
Reverse primers 10pmol/ μL 1.5
Genomic DNA 0.5 μg/ μL 4
Taq polymerase 5 U 0.5
Water 29.5
Total volume 50Μl
67
Figure 3.10.5.2. Optimized condition of PCR (polymerase chain reaction) for (hup B) gene amplification (Annexure XII).
68
3.10.6. Molecular differentiation of M. tuberculosis and M. bovis
PCR amplified products of the M. tuberculosis and M. bovis were generated by using a single set of PCR primers (M and S) as described in Figure 3.10.6 below. The genomic DNA isolated from sputum samples of pesticide exposed spray workers (n = 200) as well as healthy unexposed individuals (n = 100) was used as template to detect and differentiation of M. tuberculosis and M. bovis by adopting the procedure of Prabhakar et al. (2004). All samples were checked by PCR. In PCR, the primers M 5’ GCAGCCAAGAAGGTAGCGAA 3’ and S 5’ GTATCCGTGTGTCTTGACCTATTTG 3’ were used to generate amplicons of sizes 318 and 291 bp which represented M. tuberculosis and M. bovis, respectively.
Figure 3.10.6: Physical location of M and S primers used to detect M. tuberculosis and M. bovis.
69
3.10.6.1. Gene clean of amplified DNA fragment for sequencing
DNA fragment sequencing from the agarose gel was excised with a clean, sharp scalpel. Gel slice was weight out in a colorless tube. Three volumes buffer QG (5.5 M guanidine thiocyanate, 20 mM Tris HCl pH 6.6) was added to 1 volume gel and incubated at 50°C for 10 min; tube was vortexed every 2–3 min to dissolve gel. After the gel slice had dissolved completely, the color of the mixture turned yellow as to the colour of buffer QG without dissolved agarose. Five hundred μL buffer QG was added to the QIA quick column and centrifuged at 13,000 rpm for 1 min. Flow was discarded through placing the QIA quick column back into the same tube. For washing 750 μL buffer PE (10 mM Tris-HCl pH 7.5, 80% ethanol) was added to QIA quick column and centrifuged it again at 13,000 for 1 minute (let the column standed for 2–5 min). QIA quick column was centrifuged in the 2 mL collection tube for 1 min to remove residual wash buffer. QIA quick column was placed into a clean 1.5 ml micro centrifuge tube. To elute DNA 50 μL buffer EB (10 mM Tris・Cl, pH 8.5) was added to the center of the QIA quick membrane and the column centrifuged for 1 min. After the addition of buffer EB to the QIA quick membrane incubated it for 4 minutes and purified DNA was obtained.
3.10.6.2. Sequencing of selected samples
Among samples which were found positive for M. tuberculosis, 10 samples were sequenced by the same M and S primers which produced 318 bp product sizes in PCR. The PCR products were subjected to gene clean by adopting the procedure of QIA quick gel extraction kit (Qiagen, USA). The samples were sequenced from 1st base (Singapore) and sequencing results were aligned by ClustalW software to confirm the sequences the identity of sequences.
3.11. Statistical analysis
The data obtained from different experiments and questionnaires were analyzed by using Statistical Package for Social Sciences (SPSS version 21). One-way ANOVA was carried out to determine mean, standard deviation, standard error values concerning the data where possible.
70
RESULTS
4.1. Demographic features of agricultural spray workers of District Gujranwala.
The respondents were classified on the basis of their age. The age range of the maximum number of male participants (34%) directly involved in spraying activities from twenty years was 41-50 years and the age range of female participants (32%) was31-40 years (Figure 4.1.).
Figure 4.1: Age groups and percent population of agricultural spray workers of District Gujranwala, Punjab, Pakistan.
71
4.2. Educational level of workers by gender.
The respondents were classified on the basis of years of their education. They were categorized into groups, i.e., non-educated or illiterate, primary grade (1-5), elementary grade (6-8), secondary grade (9-10), higher secondary grade (11-12), undergraduate grade (> 12). Results related to the educational levels of the participants showed that 2 (1.33%) male and 1 (2%) female had an undergraduate education, while among the remaining respondents 67 (44.6%) males had no formal education. Among female spray workers 17 (34%) got the primary grade (1-5 years) education as shown in Figure 4.2.
Figure 4.2: Educational level and percent population of agricultural spray workers of District Gujranwala, Punjab, Pakistan.
72
4.3. Awareness and practices of use of pesticides by gender.
The results revealed that 129 (86 %) male spray workers and 44 (88%) female spray workers had information about safety; 22 (15%) males and 5 (10%) females spray workers answered that they could read instructions on the pesticides containers before use. However, 61 (40.9%) males and 14 (28%) females could understand the instructions for use of pesticides. One hundred twenty eight (85%) males and 31 (62%) females spray workers had knowledge about the use of natural fertilizers and had the information about the increasing agricultural productivity through the use of natural and chemical fertilizers. Among the spray workers when data regarding their knowledge as to if they sprayed opposite to the wind direction would that enhance the exposure to pesticides were collected through questionnaire survey then 105 (70%) males and 32 (64%) females respondents described that they ever be familiar with concept of wind direction while spraying shown in Figure 4.3.
Figure 4.3: Awareness about use of pesticides and percent population of the agricultural spray workers of District Gujranwala, Punjab, Pakistan.
73
4.4. Personal protection equipment and clothing while spraying
Handling of pesticides and application requires the use of appropriate personal protection. This involves use of gloves, masks, and wearing overall. From this figure, it is evident that few workers used the cotton overall 45 (29.5%) males and 14 (28%) females used the personal protective equipment. Gloves were used by 26 (16.5%) males and 16 (32%) females, hats by 57 (38%) male spray workers and 29 (58%) female spray workers, boots by 102 (68.0%) males and 21 (41%) females, glasses used by 46 (31%) males and 14 (28%) females, while 20 (12.5%) males and 3 (6%) females used masks as shown in Figure 4.4.1.
Figure 4.4.1. Use of personal protective equipment and percent population of the agricultural spray workers of District Gujranwala, Punjab, Pakistan.
74
Figure 4.4.2.a: Improper handling and direct exposure of a spray worker during field application of a pesticide.
Figure 4.4.2.b: A spray worker in the field without using any personal protective equipment (gloves, masks, handkerchief and boots). 75
4.5. Pesticides related acute health problems
Pesticides-related acute health problems as reported in results indicated that females were more sensitive and suffered more from health problems as compared to male spray workers. When comparing workers using protective equipment with those who had adopted less personal protective equipment, acute and chronic health hazards were observed among the latter. It was observed through questionnaire survey that 174 (87%) males and 40 (80%) females felt discomfort after spraying. Relatively few acute signs or symptoms were reported as compared to chronic manifestations by the agricultural spray workers. Twenty one (32%) males and 29 (58%) females had symptoms of headache; 33 (22%) males and 21 (42%) females had feeling of vomiting; 21 (32%) males and 14 (28%) females felt skin irritation after and during spraying, and 58 (45%) males and 15 (30 %) females were suffering from cough (Figure 4.5.1.) All these manifestations were indicator of pesticides toxicity and their susceptibility to chronic disease.
Figure 4.5.1. Health hazards and percent population of agricultural spray workers of District Gujranwala, Punjab, Pakistan.
76
Figures 4.5.2. a- 4.5.2 f. Signs and symptoms of pesticides toxicity caused by direct exposure to pesticides.
Figure (4.5.2.a-c): Allergic contact dermatitis
Figure (4.5.2.d): Mouth inflammation and ulcers
Figure (4.5.2.e): Psoriatic nail disease
Figure (4.5.2.f): Photosensitization dermatitis 77
4.6. Hematological profiles of agricultural spray workers
4.6.1. Complete blood profile of male agricultural spray workers and non -spray workers:
Complete blood analysis of male and female spray workers who were directly exposed to pesticides while applying pesticides primarily onwheat, corn, and rice crops compared to controls (non-spray workers in the fields but residents of that area) of District Gujranwala was carried out by the method as already described. . Results of male and female workers showed that there was no significant difference in blood parameters: Mean corpuscular volume (MCV), Mean corpuscular hemoglobin (MCH), MCHC Mean corpuscular hemoglobin concentration (MCHC), Platelets and Lymphocytes between the two groups as shown in Figure 4.6.1; however, WBC and RBC levels jn the blood of male spray workers and corresponding control subjects were significantly different (P < 0.05) (Table 4.6.1). Table 4.6.1: Analysed hematological parameters of male pesticidal spray workers as compared to corresponding controls (non spray workers) in District Gujranwala, Punjab, Pakistan.
Spray workers (n = 150) Control subjects (non-spray workers;n = 50) Parameters Normal Minimum- Minimum- Mean±SE SD Mean±SE SD P-value (Units) range Maximum Maximum WBC×103µL 5-11 7.30±0.16** 7.0-7.66 1.99 6.1±0.21 5.6-6.5 1.5 0.000
RBC×106µL 4-6 4.67±0.04** 4.59-4.75 0.59 5.0±0.05 4.9-5.2 0.40 0.000
HGB (g/dL) 11.5-17.5 13.2±0.12 12.9-13.4 1.4 13.0±0.18 12.6-13.4 1.3 0.503
HCT (%) 35-52 44.2±0.34 43.7-45.0 4.2 44.4±0.44 42.9-44.9 3.4 0.468
MCV(Fl) 80-100 83.1±0.61 81.9-84.3 7.5 81.2±0.89 79.4-83.02 6.3 0.111
MCHC(g/dL) 32-36 30.4±0.21 29.7-30.8 2.6 30.5±0.36 29.7-31.2 2.5 0.905
LYMPHOCYTE 20-45 63.8±0.18 63.1-64.1 2.2 63.8±0.31 63.1-64.4 2.1 0.999 (%)
NEUT (%) 45-76 64.5±0.82 59.3-66.1 10.1 62.0±1.3 59.3-64.7 7.7 0.132
PLT×103µL 150-400 178±2.2 171.8-183.2 27.9 174±2.6 171-187 26.1 0.888 **Highly significant (P < 0.05) SE = Standard Error SD = Standard Deviation 78
4.6.2. Complete blood profile of female agricultural spray workers and corresponding female control subjects:
Hematological profile of female spray operators and corresponding female control subjects revealed no significant difference in blood parameters: RBC (Red Blood Cells), HB, HCT, MCV (Mean corpuscular volume), MCH (Mean corpuscular hemoglobin), MCHC (Mean corpuscular hemoglobin concentration), PLT (Platelets) and LYM (Lymphocytes); however, WBC and NEUT (Neutrophils) levels of female spray workers and corresponding control subjects were significantly different at P < 0.05 (Table 4.6.2.). Table 4.6.2: Hematological parameters of female agricultural spray workers and corresponding control subjects (nonspray workers) in District Gujranwala, Punjab, Pakistan.
Spray workers (n = 50) Control subjects (non-spray workers; (n= 50) Parameters Normal Mean±SE Minimum- SD Mean±SE Minimum- SD P-value (Units) range Maximum Maximum
WBC×103µL 5-10 6.72±0.35** 6.0-7.4 2.5 5.3±0.06 5.1-5.4 0.49 0.000
RBC×106µL 4-5.3 4.64±0.06 4.5-4.7 .45 4.8±0.09 4.6-5.0 0.68 0.113
HB (g/dL) 11-14 13.3±0.23 12.8-13.8 1.6 13.6±0.2 13.2-14.0 1.4 0.393
HCT (%) 34-50 43.8±0.56 42.7-45.0 3.9 43.4±0.50 42.4-44.4 3.5 0.538
MCV (Fl) 76-96 82.1±1.0 80.1-84.0 7.1 82.5±0.93 80.6-84.4 6.6 0.788
MCHC (g/dL) 30-35 30.8±0.38 30-31.5 2.7 30.1±0.38 29.3-30.8 2.7 0.213
LYMPHOCYTE (%) 17-44 63.7±0.32 63-64.3 2.3 63.9±0.33 63.2-64.6 2.3 0.640
NEUT (%) 40-75 61.9±1.8** 58.2-65.6 13.1 56.2±0.54 55.1-57.4 3.8 0.004
plt×103µL 166-308 178±2.6 170-186.7 28.3 173±3.3 167-180 23.7 0.347
**Highly significant (P < 0.05) SE = Standard Error SD = Standard Deviation
79
Figure 4.6.1: Graphical comparison (Box-Whisker Plots) of the following mean hematological indices: WBC, RBC, HGB, HCT, MCV, MCHC, LYM, NEUT & PLT, between female and male pesticidal spray operators.
Legends: 1: Group of male pesticidal spray operators ; 2: Group of female pesticidal spray operators.
80
4.7. Analysis of serological parameters of agricultural spray operators
4.7.1. Comparison between liver enzymes ALT (Alanine Amino Transferase) and AST (Aspartate Aminotransferase) in male agricultural spray operators and corresponding controls.
Highly significant differences in ALT and AST values between spray operators and their corresponding control subjects as shown in results were an indication of liver dydfunction of agricultural spray operators. Liver ALT (P = 0.058 ) and AST (P = 0.006) values of male workers were significantly different from unexposed persons (Table 4.7.1).
Table 4.7.1: Level of liver enzymes ALT and AST in male spray operators and their corresponding control subjects
Spray operators (n = 50) Control subjects (n = 50) Parameters Normal Mean±SE Minimum- SD Mean±SE Minimum- SD p-value (Units) range Maximum Maximum
ALT (U/L) Upto 30 33.3±0.40** 28-39 2.8 29.1±0.26 26-36 1.8 0.000
AST (U/L) Upto 35 33.4±0.53** 24-39 3.7 26.5±0.46 20-32 3.2 0.000
**Highly significant (P < 0.05).
4.7.2. Liver enzymes, ALT and AST, in female agricultural spray operators in comparison to control females:
In female spray operators, both ALT and AST levels were significantly different (P = 0.000) as compared to female control subjects (Table 4.7.2.) Among all significant differences, AST level significantly increased in females workers exposed to pesticides as compared to the female control subjects (Figure 4.7.1.) Table 4.7.2: Levels of liver enzymes, ALT and AST, in female spray operators and corresponding control subjects.
Spray workers (n = 150) Non-spray workers (n = 50) Parameters Normal Mean±SE Minimum- SD Mean±SE Minimum- SD p-value (Units) range Maximum Maximum
ALT (U/L) Upto 40 32.6±0.26 24-40 3.2 31±0.47 24-40 3.3 0.058
AST (U/L) Upto 45 29.1±0.41** 20-39 5.1 27±0.55 20-34 3.9 0.006 81
Figure 4.7.1: Graphical comparison (Box-Whisker plots) of mean ALT and AST values between male and female pesticidal spray operators.
Legends: 1: Group of pesticides-exposed male workers; 2: Group of pesticides- exposed female workers
82
4.8: Acetylcholinestrase standardization
During this study, electric eel AChE activity was standardized by using the Amplex Red reagent kit as prescribed protocol in materials and methods section showing that each reaction contained 50 μM acetylcholine, 200 μM Amplex Red reagent, 1 U/mL HRP, 0.1 U/mL choline oxidase and the indicated amount of AChE in 1X reaction buffer. Reactions were incubated at room temperature. After 15 minutes, fluorescence was measured in a fluorescence microplate reader (ELx 800 ELISA reader, BioTek Instruments, Winooski, VT, USA) using excitation at 560 ± 10 nm. Standard curve was plotted between fluorescence of AChE analytes detected by ELISA reader and known concentrations (1, 0.5, 0.25, 0.125,0 .062, 0.031, 0.015) of AChE analytes as shown in Figure 4.8. Standard curve values were used as reference values to calculate the unknown AChE concentrations in serum samples of spray workers.
Figure 4.8: Relationship between acetylcholinestrase concentration and fluorescence detected by fluorescence microplate reader at 560 ± 10 nm.
83
1 0.5 0.25 0.125 0.062 0.031 0.015
Figure 4.8.1: Acetylcholinestrase activity of seven different concentrations (1, 0.5, 0.25, 0.125, 0.062, 0.031, 0.015) of prepared working solution of analytes) based on colorimetric assay principle (Ellmans method) measured at 560 nm in fluorescence microplate reader (ELx 800 ELISA reader).
84
Figure 4.8.2. Acetylcholinestrase activity in blood serum based on colorimetric assay principle (Ellmans method) measured at 560 nm in fluorescence microplate reader (ELx 800 ELISA reader). Key: A1-D12 = Spray workers (male) E1-G12 = Spray workers (female) H1-H6 = Non-spray workers (male) H7-H12 = Non-spray workers (female)
85
Figure 4.8.3. Acetylcholinestrase activity in blood serum based on colorimetric assay principle (Ellmans method) measured at 560 nm in fluorescence microplate reader (ELx 800 ELISA reader). Key: A1-E12 = Spray workers (male) F1-H4 = Spray workers (female) H5-H8 = Non-spray workers (male) H9-H12 = Non-spray workers (female)
86
4.9: Biochemical analysis of acetylcholinestrase
The activity level of serum AChE, standard deviation, and minimum and maximum range in control group and various spray workers exposed to different pesticides was analyzed. Due to cumulative effect of various pesticides in spray operators, AChE level was found to be significantly lower in each category of pesticides-exposed spray workers.
4.9.1. Analysis of level of acetylcholinestrase concentration in blood serum of male spray workers
ANOVA revealed significant difference (P < 0.05) between serum AChE level in male spray workers compared to corresponding control subjects. The mean AChE level in male spray workers was 0.16 U/mL and in non-spray workers was 0.44 U/mL (Table 4.9.1). Table 4.9.1: Acetylcholinestrase concentration level in male spray workers and their corresponding control subjects
Mean Unit value SE Mean F Category n (U/mL) SD Median Mean Min Max Range Square value Sig.
Spray 150 0.16 0.22 0.08 0.02 -0.10 0.66 0.76 2.81 workers Non- 62.3 0.00** spray 50 0.44 0.19 0.43 0.03 0.01 0.93 0.93 0.045 workers **Highly significant (P < 0.05)
87
4.9.2: Analysis of level of acetylcholinestrase concentration in blood serum of female spray workers.
Depressed level of activity of AChE in female spray workers was also discovered compared to their corresponding control subjects ANOVA indicating highly significant (P < 0.05) reduced level of AChE among female spray workers and their correspondiing non-spray workers. The mean AChE value in female spray workers was 0.41 U/mL compared to 0.65 U/mL in non-spray female workers (Table 4.9.2).
Table 4.9.2. Level of Acetylcholinestrase concentration in female spray workers and their corresponding controls Mean unit value SE Mean F Category n (U/mL) SD Median Mean Min Max Range square value Sig.
Spray 50 0.41 0.24 0.08 0.03 0.06 0.93 0.87 1.42 workers 16.31 0.00** Non spray 50 0.65 0.33 0.43 0.04 0.32 1.63 1.31 0.087 workers **Highly significant (P < 0.05)
88
4.10. Immunoglobulins concentration in blood serum of male spray workers
The concentration level of various immunoglobulins (IgA, IgM, IgE) showed significant differences: serum immunoglobulins mean values in male spray workers and non-spray workers as compared to the reference values. The concentration of immunoglobulins IgA and IgM were significantly different in male spray workers as compared to male non-spray workers but the IgE level was not significantly different between the workers and non-workers
4.10.1. Statistical analysis of immunoglobulins
Serum immunoglobulins concentration mean values of spray workers and non-spray workers indicated that immunoglobulins, IgA and IgM, were significantly different in spray workers as compared no non-spray workers but IgE levels was not significantly different in both male and female spray workers and their corresponding control subjects (Table 4.10.1.1 and Table 4.10.1.2).
Table 4.10.1.1 Levels of immunoglobulin in blood serum of males agricultural spray workers exposed to pesticides as compared to non-spray workers of District Gujranwala, Punjab, Pakistan.
Female spray workers (n= 50) Female non spray workers (n = 50) Parameter Normal Mean Mean Minimum- SD Mean Mean Minimum- SD df p- (Units) range values square Maximum values square Maximum value (mg/dL) (mg/dL) IgA 70-400 350.3 5512.6 201-440 36.7 341 1154.8 302-332 9.1 1 0.033 (mg/dL) ** IgM 40-230 157 6093 108-171 16.1 119 225.5 103-123 6.0 1 0.000 (mg/dL) ** IgE <.023 0.027 0.001 0.01-.027 0.035 0.019 0.000 0.02-0.14 0.03 1 0.928 (mg/dL)
**Highly significant (P < 0.05)
Note: The normal range of reference values in healthy individuals as mentioned by (Aroonvilairat et al., 2015)
89
Table 4.10.1.2. Levels of immunoglobulins in blood serum of female agricultural spray workers exposed to pesticides as compared to non-spray workers of District Gujranwala, Punjab, Pakistan.
**Highly significant (P < 0.05)
Note: The normal rage of reference values in healthy individuals as mentioned by
Female Spray workers (n = 50) Female non-spray workers (n = 50) Parameter Normal Mean Mean Minimum- SD Mean Mean Minimum- SD df P- (Units) range values square Maximum values square Maximum value (mg/dL) (mg/dL) IgA (mg/dL) 70-400 348.76 18117 299-440 26.29 336 724 201-325 28.9 1 0.000 ** IgM (mg/dL) 40-230 161.6 9400 108-182 17.2 124.6 248 103 139 1 0.000 ** IgE (mg/dL) 0.032 0.001 0.01-0.28 0.04 0.015 0.645 0.01 0.14 1 0.425 <0.023 Aroonvilairat et al., (2015).
90
4.10.2. Level of immunoglobulin IgA
The level of immunoglobulin IgA shown in Figure 4.10.2 reveals that among male and female spray workers the range was normal but differed significantly between male spray workers and their corresponding non-spray workers (control).
IgA
355 350 345 Male spray workers 340 Male non spray workers 335 Female spray workers 330 Female non spray workers 325 Male spray Male non Female Female non Level of immunoglobulin of Levelimmunoglobulin (mg/dL) workers spray spray spray workers workers workers
Figure 4.10.2: Levels of immunoglobulin IgA, among male and female spray workers and non-spray workers (corresponding controls).
91
4.10.3. Level of immunogloublin IgM
The level of immunoglobulin, IgM, shown in Figure 4.10.3 reveals that in male spray workers level of IgM was raised above the normal value. Also, statistically significant difference was found between male spray workers and non-spray workers (controls). In females, level of immunoglobulin IgM also differed among spray workers and non-spray workers (their corresponding controls).
Figure 4.10.3: Levels of immunoglobulin IgM, in male and female pesticides spray workers and non spray workers (corresponding controls).
92
4.10.4. Levels of immunogloublin IgE
The level of immunoglobulin IgE shown in Figure in 4.10.4. in male and female spray workers and and their corresponding controls revealed that level of IgE was raised above the normal value with significant difference between male spray workers and male non-spray workers (their corresponding controls) as well as in female spray workers and female non-spray workers (controls).
Figure 4.10.4: Levels of immunoglobulin IgE among male and female spray workers and their non-spray workers (corresponding controls).
93
4.11. Standaridization of HPLC
HPLC system was standardized to check the performance of column and detector of mobile phase on resolution and linearity. To evaluate the above parameters standard solutions of pesticides were used. Methanol/water and acetonitrile/water were used as mobile phase for validation of instrument as well as analysis of pesticides residues in serum of spray workers . Chromatogram of technical grade standards (dichlorovos, profenofos, chlorpyrifos, malathion and imidacloprid) obtained at optimized conditions are given below in Figures 4.11.1 to 4.11.5. Representative chromatograms of the spray workers deprotenized blood serum are shown in Figures 4.11.6 to 4.11.29.
Figure 4.11.1: Chromatogram of technical grade standard of dichlorovos analyzed by reverse phase HPLC. RT of dichlorovos was: 4.2 min. Mobile phase: 94 acetonitrile: water 92:8, UV: 254 nm. Flow rate: 0.85mL/min, injection volume: 10µL. (Note: scale was the same on both sides of the y-axis).
Figure 4.11.2: Chromatogram of technical grade standard of profenophos analyzed by reverse phase HPLC. RT of profenophos was: 4.1 min. Mobile phase: acetonitrile: water 65:35, UV: 282 nm, flow rate, 2mL/min, and injection volume: 10µL. (Note: scale was the same on both sides of the y-axis).
95
Figure 4.11.3: Chromatogram of technical grade standard of chlorpyrifos analyzed by reverse phase HPLC. RT of chlorpyrifos was: 12 min. Mobile phase: acetonitrile: water 70:30, UV: 230 nm. Flow rate: 2mL/min, injection volume: 10µL. (Note: scale was the same on both sides of the y-axis).
96
Figure 4.11.4: Chromatogram of technical grade standard of malathion analyzed by reverse phase HPLC. RT of malathion was: 7.3 min. Mobile phase: acetonitrile: water 24:76, UV: 260nm, flow rate, 1mL/min, injection volume: 10µL. (Note: scale was the same at y- axis on both sides of the chromatogram).
97
Figure 4.11.5: Chromatogram of technical grade standard of imidacloprid analyzed by reverse phase HPLC. RT of imidachloprid was: 11.2 min. Mobile phase: acetonitrile: water 70: 30, UV: 270 nm, flow rate: 2mL/min, injection volume: 10µL. (Note: scale was the same on both sides of the y-axis).
98
Figure 4.11.6: Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of chlorpyrifos (RT=12).
99
Figure 4.11.7. Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of malathion (RT=7.3).
100
Figure 4.11.8. Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of malathion (RT=7.3).
101
Figure 4.11.9. Liquid chromatogram of blood serum of spray worker exposed to pesticides show detection of profenophos (RT= 4.1).
102
Figure 4.11.10: Liquid chromatogram of blood serum of spray worker exposed to pesticides show detection of imidacloprid (RT=11.2).
103
Figure 4.11.11: Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of malathion (RT= 7.3).
104
Figure 4.11.12: Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of residues of many pesticides.
105
Figure 4.11.13: Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of profenophos (RT= 4.1).
106
Figure 4.11.14: Liquid chromatogram of blood serum spray worker exposed to pesticides show the detection of malathion (RT= 7.3).
107
Figure 4.11.15. Liquid chromatogram of blood serum of spray workers exposed to pesticides show detection of residues of several pesticides.
108
Figure 4.11.16. Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of residues of several pesticides.
109
Figure 4.11.17: Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of chlorpyrifos (RT=12).
110
Figure 4.11.18. Liquid chromatogram of blood serum of pray worker exposed to pesticides show the detection of chlorpyrifos (RT=12).
111
Figure 4.11.19: Liquid chromatogram of blood serum of spray worker exposed to pesticides show the detection of malathion (RT=7.3).
112
Figure 4.11.20. Liquid chromatogram of blood serum of male spray workers exposed to pesticides show detection of malathion (RT=7.2).
113
Figure 4.11.21. Liquid chromatogram of blood serum of spray worker exposed to pesticides show detection of imidacloprid (RT=11.2).
114
Figure 4.11.22: Liquid chromatogram of blood serum of spray worker exposed to pesticides show detection of residues of several pesticides.
115
Figure 4.11 23. Liquid chromatogram of blood serum of spray worker exposed to pesticides show detection of dichlorovos (RT=4.2).
116
Figure 4.11.24. Liquid chromatogram of blood serum of spray workers exposed to pesticides show the detection of residues of several pesticides.
117
Figure 4.11.25. Liquid chromatogram of blood serum of male spray workers exposed to pesticides show detection of malathion (RT=7.3).
118
Figure 4.11.26. Representative Liquid chromatogram of blood serum of non- spray workers (control group) Mobile phase= acetonitrile: water 65:35, UV: 282 nm, flow rate=2 mL/min, injection volume=10 µL.
119
Figure 4.11.27. Representative Liquid chromatogram of blood serum of non- spray workers (control group) Mobile phase = acetonitrile: water 70:30, UV: 230 nm, flow rate = 2 mL/min, injection volume = 10 µL.
120
Figure 4.11.28. Representative Liquid chromatogram of blood serum of non- spray workers (control group) Mobile phase = acetonitrile: water 24:76, UV: 260 nm, flow rate = 1 mL/min, injection volume = 10 µL.
121
Figure 4.11.29. Representative Liquid chromatogram of blood serum of non- spray workers (control group) Mobile phase = acetonitrile: water 8:92, UV: 230 nm, flow rate = 0.85 mL/min, injection volume = 10 µL.
122
4.12. Pesticide residues detecteion and quantification blood serum of spray workers
The detection limit of pesticides varies in serum of spray workers. Multiple pesticides residues were detected in their blood serum. Number of spray workers (male and female) with positive concentration of OP pesticides residues in their serum is shown in Table 4.12.
Table 4.12. Number of spray workers with positive concentration of pesticides.
Name of pesticides Male spray workers Females spray workers (n=150) (n=50) Pesticide (A) 12 (8%) 7 (14%) Pesticide (B) 9 (6%) 3 (6%) Pesticide (C) 25 (16.6%) 0 (0%) Pesticide (D) 18 (12%) 3 (6%) Pesticide (E) 0 (0%) 2 (4%) Pesticide (AB) 31 (20.6%) 2 (4%) Pesticide (BC) 6 (4%) 0 (0%) Pesticide (CD) 11 (7.3%) 1 (2%) Pesticide (DE) 0 (0%) 2(4%) Pesticide (DA) 5 (3.3) 0 (0%) Pesticide (AC) 4 (2.6%) 2 (4%) Key: Pesticide A= Chlorpyrifos Pesticide B= Profenophos Pesticide C= Imidacloprid Pesticide D= Malathion Pesticide E= Dichlorovos
123
4.12.1. Descriptive statistical data of pesticides quantification in serum samples of spray workers by high performance liquid chromatography.
Pesticides residues were detected in blood serum samples of spray workers by using high performance liquid chroatography. Descriptive statistical data of pesticides residues detected in serum samples were computed statistically. Level of pesticides residues in male spray workers are shown in Table 4.12.1.1. While in female spray workers are shown in Table 4.12.1.2.
Table 4.12.1.1: Descriptive statistical data of pesticides residues detected in serum samples of male spray workers.
Name of pesticides Range detected SE (µg/L) Minimum Maximum Sum mean SD Variance
Chlorpyrifos 1.40 0.00 1.40 2.40 0.07618 0.32319 0.104 Profenophos 1.29 0.01 1.30 6.10 0.16729 0.55482 0.308 Imidacloprid 0.41 0.00 0.41 2.97 0.02350 0.11749 0.014 Malathion 1.40 0.00 1.40 3.33 0.12445 0.44871 0.201
Table 4.12.1.2: Descriptive statistical data of pesticides residues detected in serum samples of female spray workers.
Name of pesticides Range SE detected (µg/L) Minimum Maximum Sum mean SD Variance
Chlorpyrifos 1.39 0.01 1.40 1.72 0.19292 0.51043 0.261 Profenophos 1.23 0.02 1.25 1.35 0.40037 0.69347 0.481 Dichlorovos 0.03 0.02 0.05 0.07 0.01500 0.02121 0.000 Malathion 1.09 0.01 1.10 1.47 0.20266 0.45317 0.205
124
4.13. Detection of different species of mycobacteria
4.13.1. DNA isolation and quantification In order to detect the type of Mycobacterium involved in MDR-TB, the genomic DNA was isolated from cultured sputum samples of all ninety one patients. The genomic DNA was isolated by GF-I DNA extraction kit method (Vivantis Inc., USA) as well as PUREGENE kit method (Elpis Biotech Inc., South Korea). Both methods provided equally good results. The intact genomic DNA was observed in all samples and 15 kb size genomic DNA band was detected (Figure 4.13.1.). The quantity of extracted genomic DNA for the samples was found to be in the range of 0.1-0.5 µg/µL based on taking OD at 260 nm. The 260/280 ratio was also determined for all samples and it was found to be 1.5-2.0 which indicated that genomic DNA from all samples was suitable to be used further in downstream analysis.
Figure 4.13.1: Representative photograph showing DNA isolation from sputum culture samples. Key: Lane 1-7: DNA isolation from sputum samples of agricultural worker with confirmed tuberculosis; M: 1 Kb DNA ladder, (Cat No. EBM 1003, Elpis Biotech Inc., South Korea).
125
4.13.2. Molecular differentiation of M. tuberculosis and M. bovis PCR with the use of primer set N & S. The primers M 5’GCAGCCAAGAAGGTAGCGAA 3’ and S 5’ GTATCCGTGTGTCTTGACCTATTTG 3’ were used to generate amplicons of sizes 318 and 291 bp which represented M. tuberculosis and M. bovis, respectively. The optimized annealing temperature for primer M and S was 59 0C. In the current research by using primers M and S sputum culture samples of spray workers (males/females) were analyzed by polymerase chain reaction for molecular detection of M. tuberculosis (318 bp) and M. bovis (291 bp). Amplified fragments were observed on 1 % agarose gel as shown in (Figure 4.13.2).
M 1 2 3 4 5 6 7 8 9 10 11
300bp 318 bp 291 bp
Figure 4.13.2. Agarose gel (1.5%) showing differentiation of M. tuberculosis and M. bovis by PCR using primer set M and S. Key:Lanes 1-7 and 9-10: Samples found positive for M. tuberculosis; Lane8: Samples found positive for M. bovis; Lane 11: Negative control; M: GeneRuler 100 bp DNA Ladder, Cat No. SM0241, Thermo Fisher Scientific Inc., USA.
126
4.13.3. Molecular detection of M. tuberculosis and M. bovis in pesticides exposed workers.
M. tuberculosis was detected in (23/150) 15% male spray workers and (18/50) 36% female spray workers, while M. bovis was detected in (8/150) 5% male spray workers and (5/50) 10% female spray workers (Table 4.13.3) by targeting histone like protein (hupB) gene. In control group of non-spray workers of both females and males no tuberculosis infection was diagnosed by the molecular test. No mutation detected in hupB gene. The strains were found to be M. tuberculosis and very few M. bovis among all sprayers. A chi-square test indicated that there existed a significant different (P = 0.000) between positive M. tuberculosis and negative M. tuberculosis in male spray workers out of total (Chi-square: 72.107) and also between positive M. bovis and negative M. bovis in male spray workers out of total (Chi-square: 119.707).
Table 4.13.3: Molecular detection of M. tuberculosis and M. bovis in pesticides- exposed workers.
M. tuberculosis M. bovis Pesticide Prevalence Prevalence Exposed Prevalenc P- *df Chi- Prevalenc P- *df Chi-square Groups e value square χ2 e value χ2 Male spray 23 0.000 1 72.107 8 0.000 1 119.707 workerss (15%) ** (5%) ** (n=150) Female spray 18 0.048 1 3.920 5 0.000 1 32.000 workerss (36%) ** (10%) ** (n=50)
*Degrees of freedom **Highly significant (P < 0.05)
Note: In control group of non-spray workers of both females and males no TB infection was diagnosed by using molecular test. 127
4.13.4. Sequencing of targeted hup B gene Sequences show absolute homology of targeted hup B gene by homology sequencing. Ten samples where 318 bp fragments were amplified by using primers M and S in PCR were chosen randomly. The samples numbers were 4, 7, 9A, 56, 81, 55, 38, 80, 62, 24.
>Ref1 (M. bovis) (Hlp gene, accession no. Y18421) cagaaggacccgctgttaagcgtggtgtgggggccagtgcagccaagaaggtagcgaagaaggcacctg ccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaagg cgcccgccaagaaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaaga ccgcggtcaaggcatctgtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggc cggctaccaaggctcccgccaagaaggcagccgctcggcggggtcgcaaatag
>Ref2 (M. tuberculosis) (M. tuberculosis strain PR10 genome Sequence ID: CP010968.1) cagaaggacccgctgttaagcgtggtgtgggggccagtgcagccaagaaggtagcgaagaaggcacctgccaagaa ggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaa gcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtga agaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggcc ggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaatag
>80F Gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgccaggaaggcggcgaccaag gcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccgcc aagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaaggcg ccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggcgg ggtcgcaaataggtcaagacacacggatac
>80RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>81F gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgccaggaaggcggcgacca aggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccg ccaagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaagg cgccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggc ggggtcgcaaataggtcaagacacacggatac
>81RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>04F gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgccaggaaggcggcgaccaag gcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccgcc aagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaaggcg ccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggcgg ggtcgcaaataggtcaagacacacggatac
128
>04RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>07F gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgccaggaaggcggcgaccaag gcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccgcc aagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaaggcg ccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggcgg ggtcgcaaataggtcaagacacacggatac
>07RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>9AF gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgccaggaaggcggcgaccaag gcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccgcc aagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaaggcg ccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggcgg ggtcgcaaataggtcaagacacacggatac
>9ARC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>56F gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgccaggaaggcggcgaccaag gcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccgcc aagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaaggcg ccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggcgg ggtcgcaaataggtcaagacacacggatac
>56RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>55F gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgccaggaaggcggcgacca aggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccg ccaagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaagg cgccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggc ggggtcgcaaataggtcaagacacacggatac
>55RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag 129 gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>38F gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgccaggaaggcggcgacca aggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccg ccaagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaagg cgccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggc ggggtcgcaaataggtcaagacacacggatac
>38RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>62F gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgccaggaaggcggcgacca aggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccg ccaagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaagg cgccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggc ggggtcgcaaataggtcaagacacacggatac
>62RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
>24F gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgccaggaaggcggcgacca aggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaagctgtcaaggccacgaagtcacccg ccaagaaggtgaccaaggcggtgaagaagaccgcggtcaaggcatcggtgcgtaaggcggcgaccaagg cgccggcaaagaaggcagcggccaagcggccggctaccaaggctcccgccaagaaggcaaccgctcggc ggggtcgcaaataggtcaagacacacggatac
>24RC gcagccaagaaggtagcgaagaaggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgacc aaggcgcccgccaggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaag aaagctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcggtcaag gcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagcggccggctaccaag gctcccgccaagaaggcaaccgttcgggggggtcgcaaatag
CLUSTAL O(1.2.3) multiple sequence alignment
Ref1 cagaaggacccgctgttaagcgtggtgtgggggccagtgcagccaagaaggtagcgaaga Ref2 cagaaggacccgctgttaagcgtggtgtgggggccagtgcagccaagaaggtagcgaaga 80RC ------gcagccaagaaggtagcgaaga 81RC ------gcagccaagaaggtagcgaaga 04RC ------gcagccaagaaggtagcgaaga 07RC ------gcagccaagaaggtagcgaaga 9ARC ------gcagccaagaaggtagcgaaga 56RC ------gcagccaagaaggtagcgaaga 55RC ------gcagccaagaaggtagcgaaga 38RC ------gcagccaagaaggtagcgaaga 62RC ------gcagccaagaaggtagcgaaga 24RC ------gcagccaagaaggtagcgaaga 80F ------130
04F ------07F ------9AF ------56F ------81F ------55F ------38F ------62F ------24F ------
Ref1 aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaag------Ref2 aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 80RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 81RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 04RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 07RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 9ARC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 56RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 55RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 38RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 62RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 24RC aggcacctgccaagaaggcgacaaaggccgccaagaaggcggcgaccaaggcgcccgcca 80F ------gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgcca 04F ------gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgcca 07F ------gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgcca 9AF ------gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgcca 56F ------gccgagaaaaggcgacaaggccgccagaaggcggcgaccaaggcgcccgcca 81F ------gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgcca 55F ------gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgcca 38F ------gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgcca 62F ------gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgcca 24F ------gtgcaacgaaaggcgaaaaggccgccaagaaggcggcgaccaaggcgcccgcca ** *** * * * * * *****************
Ref1 ------gcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag Ref2 ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 80RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 81RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 04RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 07RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 9ARC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 56RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 55RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 38RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 62RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 24RC ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 80F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 04F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 07F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 9AF ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 56F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 81F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 55F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 38F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 62F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag 24F ggaaggcggcgaccaaggcgcccgccaagaaagcggcgaccaaggcgcccgccaagaaag *******************************************
Ref1 ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg Ref2 ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 80RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 81RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 04RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 07RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 9ARC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 56RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 55RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 131
38RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 62RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 24RC ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 80F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 04F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 07F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 9AF ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 56F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 81F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 55F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 38F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 62F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg 24F ctgtcaaggccacgaagtcacccgccaagaaggtgaccaaggcggtgaagaagaccgcgg ************************************************************
Ref1 tcaaggcatctgtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc Ref2 tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 80RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 81RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 04RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 07RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 9ARC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 56RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 55RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 38RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 62RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 24RC tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 80F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 04F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 07F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 9AF tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 56F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 81F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 55F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 38F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 62F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc 24F tcaaggcatcggtgcgtaaggcggcgaccaaggcgccggcaaagaaggcagcggccaagc ********** *************************************************
Ref1 ggccggctaccaaggctcccgccaagaaggcagccgctcggcggggtcgcaaatag---- Ref2 ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaatag---- 80RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 81RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 04RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 07RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 9ARC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 56RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 55RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 38RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 62RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 24RC ggccggctaccaaggctcccgccaagaaggcaaccgttcgggggggtcgcaaatag---- 80F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 04F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 07F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 9AF ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 56F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 81F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 55F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 38F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 62F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca 24F ggccggctaccaaggctcccgccaagaaggcaaccgctcggcggggtcgcaaataggtca ******************************** *** **** **************
Ref1 ------Ref2 ------80RC ------81RC ------04RC ------132
07RC ------9ARC ------56RC ------55RC ------38RC ------62RC ------24RC ------80F agacacacggatac 04F agacacacggatac 07F agacacacggatac 9AF agacacacggatac 56F agacacacggatac 81F agacacacggatac 55F agacacacggatac 38F agacacacggatac 62F agacacacggatac 24F agacacacggatac
Figure 4.13.4: Multiple sequences alignment of histone like protein (Hup B) gene from pesticide exposed individuals by ClustalW software. Ref1: M. bovis, Hlp gene (accession no. Y18421),. Ref2: M. tuberculosis, strain PR10 genome Sequence ID: CP010968.1. Samples from pesticide exposed individuals: 4, 7, 9A, 24, 38, 55, 56, 81, 80, 62. Blue color: Position of forward primer. Green color: Position of reverse primer.
133
DISCUSSION
The adversarial role of pesticides on human health is still controversial despite their excessive use and wide spread diffusion in environment. No previous study in Pakistan provides detailed information concerning the adverse effects of pesticides on human vital organs, such as liver, lungs, heart, skin and kidneys. In the present study, health ailment and alteration of hematological, biochemical, and immunological parameters among agricultural spray workers were determined by utilizing various advanced biochemical techniques. A pioneering aspect of this study has been the estimation of toxicity caused by the OP compounds in agricultural workers. Acetylcholinesterase level was assessed by fluorimetric method and residues of chlorpyrifos, profenophos, dichlorovos, and malathion were assessed by HPLC. Most important aspect of this study is the molecular detection of M. tuberculosis and M. bovis by targeting the hub B gene in cultured sputum samples of agricultural spray workers.The District of Gujranwala was selected for this research because pesticide spraying is a common profession in that District. However,due to long-term exposure of spray workers to pesticides, these workers suffer from several diseases with incidence of TB in that area being quite high.
The demographics data regarding age and education of agricultural spray workers of District Gujranwala collected by questionnaire survey is very important because no such information had been gathered in the past in this District concerning pesticidal spray workers . The study revealed that age of the female spray workers ranging between31-40 years were 32% and male spray workers of this age group were 26% but female spray workers of age group between41 to 50 years were 30% while male spary workers in this age range were of 34% (Figure 4.1.). This also indicates that more younger female spray worker were involved in spraying activities as compared to males. However, females had shorterterm exposure to pesticides as compared to males which finding is contradictory to the study of Naidoo et al. (2008) reporting average age of41.9 years of majority of spray workers.
The present study also revealed that literacy rate of female spray workers was higher than the male spray workers. Among the spray workers of District Gujranwala, 44% males and 12% females had no formal education (Figure 4.2.) The probable reason for this high rate of illiteracy among males in the District Gujranwala is due to fact that spray workers of the District generally belong to socio-economically poor 134 families and for the very much needed financial support of their families, male spray workers did not get any formal education and adopted the crops pesticidal spray profession at a rather early age. The spray workers with little or no formal education were at high risk because they were unable to understand safety procedures and had difficulty or inability of reading instructions on pesticide labels . However, respondents that were educated had adequate knowledge of toxic effects of pesticides on human health. These findings are consistent with those reported by Alavanja et al. (2001); Salameh et al. (2004); Atreya(2008); and Rigotto et al. (2014). Among the subjects included in this study, 15% male and 10% female were aware of the instruction regarding the pesticides usage but were reluctant to follow the instructions intentionally.
The present study further assessed the difference in attitude and response according to the gender concerning the safety measures. Although all male spray workers were dressed up properly for the spray operation, they were generally careless about the use of personal protective equipment. Results related to personal protective equipment and clothes used by the spray workers are shown in Figure 4.4. Statistics about the other personal protective equipment use revealed that gloves were used by 16.6% males and 31% females; hats by38% males and 58% females; boots by 68.0% males and 41% females; glasses by30.6% males and 28% females, and masks by12.9% males and 6.6% females. Based on these findings, It is emphasised that protective measures should be adopted by spray workers while working in agricultural fields. Risk of pesticides exposure increases during summer season because during the hot and humid tropical environment the spray workers feel uncomfortable and lazy and therefore are reluctant to wear protective gear, such as boots and face masks and thereby are vulnerable to direct absorption of pesticides through skin as well as the respiratory tract. Agricultural spray workers can protect themselves by using goggles, gloves, and masks but using such personal protective equipment affects their work efficiency and also they feel uncomfortable by using such equipment. It was discovered that nearly 50% of the adolescent pesticides sprayers had the perception that even the use of protective equipment could not save them from dangerous pesticides; therefore, they did not use them . Wilson and Tisdell (2001) had reported that protective equipment could contribute to decreasing the ill-health effects caused by pesticides. 135
During this research, it was discovered that exposure to pesticides may cause chronic and acute health problems; a variety of physical signs and symptoms were quite prevalent among the spray workers. These symptoms appeared in both male and female spray workers due to direct exposure to pesticides during and after their spraying activity. Prevalence of adverse signs and symptoms related to pesticides were higher among females as compared to males. The pesticide-exposed workers complained mostly of headache (male 32% and 57% female), nausea (68% male and 69% female), vomiting (22% male and 42% female), eye irritation (47% male and 55% female) as shown in Figure 4.5. Similar findings related to various self-reported symptoms, such as skin rash, headache, diarrhea, eye irritation, vomiting, backache due to toxicity of pesticides have been reported in several previous studies (Hoppin et al., 2002; Murphy et al., 2002; Ohayo-Mitoko et al., 2000; Smit et al., 2003; Strong et al., 2004; Del Prado-Lu, 2007). One of the significant findings of current research related to personal health of spray workers was that 45% male spray workers and 30% female spray workers suffered from cough.
Complete blood count of spray workers exposed to pesticides showed significant difference between white blood cell and red blood cell counts among male spray workers but no significant difference was observed in other parameters (Table 4.6.1.) However, among female workers, significant increase in level of white blood cells and neutrophils was noted (Table 4.6.2).. Increased neutrophils level is indicative of infection in the body. Pesticide residues affect different blood parameters, such as MCV, MCH, MCHC, Plt, RBCs and lymphocytes due to direct exposure of some workers to pesticides at their work place and frequent exposure can have cumulative effect resulting in in change in profile of blood parameters (Tokorska et al., 2004; Pastor et al., 2002; Abu-Mourad, 2005). On the other hand, Lebaillt et al. (2003), Yousaf et al. (2003), and Remor et al. (2009) had reported contradictory research results revealing no difference in blood indices due to exposure to pesticides.
Nevertheless, acute effects related to pesticides toxicity are well known and concerns about chronic health, such as neurotoxicity, carcinogenesis and immunological effects do exist. Payan-Renteria et al. (2012) had reported changes in the circulatory, neurological, digestive, renal, dermatological and reproductive systems due to exposure to pesticides. Jamil et al. (2007) had reported the increase in count of WBC of agricultural worker who were exposed to pesticides. These results are compatible 136 with findings of present research. Del Prado-Lu, (2007) had found that pesticide exposed farmers of La Trinidad (Benguet) were having most common complaints of headache and cough. Analysis showed that RBC cholinesterase levels were positively correlated with duration of pesticide exposure, containers of pesticides, and contaminated cloths with abnormal MCV. Further, significant changes were noted in the levels of RBC, PLT, WBC, HCT and HB. It was reported in agricultural workers, that increase in lymphocytes and monocytes count was significantly associated with an increase in total leucocytes count. Cumulative effect due to frequent pesticide exposure resulted in a change of blood parameters profile while Remor et al. (2009) determined that there was no difference in hematological and biochemical indices Pesticides-related hematotoxicity, including agranulocytosis, aplastic anemia, thrompopenia and neutropenia, has been previously reported The exchange of OPs with iron reduces the binding efficiency of hemoglobin with iron, leading to anemic conditions. The hematological disorders in the form of leucocytosis, leukopenia, lymphocytopenia, thrombocytopenia, monocytosis and anemia or aplastic anemia have long been reported among pesticides-exposed subjects.
Fareed et al. (2013) had also reported significant abnormal blood counts for neutrophils, hemoglobin, MCV, RBC, WBC, PLTs and MCH among north Indian pesticide sprayers as compared to controls causing respiratory problems due to exposure to pesticides. Such alterations in hematological indices of exposure to pesticides have been confirmed by decreased activities of AChE and BChE anemia and reduction in RBC counts resulting from the damaging effects of pesticidal chemicals on erythropoietic tissues. Similar variations in hematological indices have also been reported by Rastogi et al. (2008) in pesticide exposed workers.
With all such abnormalities and proliferations, there may be a risk of developing CML. Further, depletion of WBCs will result the risk of having an infection (neutropenia). Azmi et al. (2009) evaluated blood indices in workers chronically exposed to different pesticides from rural areas of Karachi and reported a high lymphocyte count along with decreased trends of the following: hemoglobin, neutrophils, MCH, RBC and MCV. Azmi et al. (2009) also reported other drastic impacts on health, such as nephritic, dermatological issues, hepatic and respiratory problems etc. from toxic chemicals of pesticides. Ismail et al. (2010) has reported 137 disorders in the hematological, hepatic and renal indices in pesticides- exposed Egyptian children.
For health safety and surveillance primary care must be taken. It has been suggested that pesticidal spray workers should periodically get themselves examined for complete blood count test and liver function screening. Periodic attention to liver investigation is given to exposed population of pesticidal spray workers by analyzing alteration in hepatic enzymes level but limited hepatic disorder were noticed. There is a requirement for appropriate tests that would provide information regarding chronic and acute toxicity of liver caused by OPs.
The present study also showed that certain enzymes were influenced by exposure to pesticides. Although in this study the mean values of ALT and AST in both male and female pesticides-exposed spray workers were higher as compared to unexposed workers, among all significant results related to ALT and AST, in female spray workers, the levels of AST were found to be higher as compared to non-spray workers (Tables 4.7.1. and 4.7.2.). Considerable increase in ALT and AST levels reveal a subtle or subclinical hepatotoxic effect of OPs on spray workers. Previously, liver dysfunction due to environmental disinfectants has been observed in agricultural workers of Israel, Italy, India, Saudi Arabia, Egypt and Pakistan (Amer et al., 2002; Patil et al., 2003; Hernandez et al., 2006; Azmi et al., 2006; Khan et al., 2008; Al- Sarar et al., 2009; Patil et al., 2009; Ibrahim et al., 2011; Cataudella et al., 2012). Liver dysfunction due to increase in these enzymes in occupationally exposed workers reported previously are in agreement with the findings of current research.
Enzymatic degradation of neurotransmitters due to exposure to OPs over excavates function of neurons resulting in paralysis, respiratory failure and death; hence, AChE was used as an index for chronic exposure to OPs in spray workers and quantitatively depressed level of AChE was assessed in the pesticides-exposed spray workers. Significant differences of male and female spray workers to corresponding non-spray workers was evaluated (P = 0.000). In male spray workers AChE was 0.16 U / mL and in non-spray workers it was 0.44 U/mL (Table 4.9.1.). In female spray workers, AChE level was 0.41 U/mL and in non- spray workers was0.65 U/mL and this difference was highly significant (P = 0.000) Table 4.9.2. This indicated that pesticidal spray workers of District Gujranwala were at higher health risk associated with exposure to OPs. o Thus, cholinesterase is one of the most important enzymes 138 required for the proper function of nervous system. The enzyme, AChE, is responsible for the expedient breakdown of the neurotransmitter acetylcholine. Due to exposure to OPs, normal transmission of nervous impulses fired in the nervous system of pesticidal spray workers result in uncoordinated muscle movement causing nausea, dizziness, and eventually seizures and unconsciousness. In a previous study, More et al. (2003) showed that spray personnel without protective clothing presented a marginal reduction in their blood cholinesterase activity during the exposure period. Due to long-term exposure to OPs, AChE enzyme inhibition resulting in the impairment of sensory and motor nerve conduction in pesticidal spray workers of Sri Lanka, India and Pakistan has been previously reported byseveral workers (e. g., Gertrudis et al., 2001; Smit et al., 2003; Karabay et al., 2004; Hernandez et al., 2004; Kesovachandran et al., 2006; Jors et al., 2006; Bhalli et al., 2006; Fareed et al., 2010; Ibrahim et al., 2011). These finding were in coincidence with the present study. There have been only a few studies undertaken in Pakistan on exposure to OP pesticides and human health; however, in the District of Gujranwala no study concerning pesticides risk assessment on serum acetyl cholinesterase activity has been previously conducted.
An important contribution of present research is the analysis of effects of pesticides on immune system of spray workers by ELISA method. Immunotoxicity in spray workers was observed to be significantly different for IgA and IgM (P = 0.033 and P = 0.000) in male spray workers and non spray-workers, respectively, for the first time. Similarly, significant difference of immunoglobulin IgM and IgA (P = 0.000 and P = 0.000) in female spray workers and non-spray workers was also observed; whereas non-significant difference was observed for IgE (P = 0.928) in male spray workers and non-spray workers. Likewise, Non- significant difference was also observed for IgE (P = 0.425) in female spray workers and female non- spray workers. The increases in level of IgM reflect chronic infection that caused the polyclonal hypergammaglobulinemia and the rise in immune response in spray workers. These discrepancies may be the result of different components in pesticides such mixtures that only certain subclass of immunoglobulin was affected by each pesticide. No previous study in Pakistan has provided information concerning the effect of pesticides exposure on the level of immunoglobulins. Findings of Undeger and Basaran (2001) are contradictory to the present study; these authors had reported no 139 changes in serum IgG, IgA, IgM and C3; however, increases in IgG4 levels and decrease in IgA level in pesticides- exposed workers were reported by Steerenberg et al. (2008) in Europe. Whereas, Aroonvilairat et al. (2015) observed elevated level of total serum IgE unlike other immunoglobulin classes in Thai orchid farmers but it is not a single diagnostic condition for testing of pesticides toxicity in agricultural workers. In Greece, occupational exposure to multiple agricultural chemicals could be related to allergic rhinitis in Greek farmers (Chatzi et al., 2007; Fukuyama et al., 2009).
In the present study, analysis of pesticides residues in blood serum of the spray workers with occupational exposure to pesticides was carried out by using high performace liquid chromatography. The analysis of serum samples revealed the presence of residues of targeted OP pesticides, i.e., profenophos, chlorpyrifos, dichlorovos, malathion as shown in Table 4.12.1. Chlorpyrifos was detected at level of 0.00-1.4µg/L; profenophos 0.01-1.30 µg/L; imidacloprid 0.00-0.14 µg/L; and malathion 0.00-1.40 µg/L but dichlorovos was not detected in blood serum samples of male spray workers. While, in female workers chlorpyrifos (0.01-1.40 µg/L) profenophos (0.02-1.25 µg/L), and malathion (0.02-0.05 µg/L), and dichlorovos (0.01-1.10 µg/L) were detected but imidacloprid was not detected.. The maximum residue of pesticides detected was of chlorpyrifos and malathion in male spray workers while in female spray workers chlorpyrifos and profenophos had the maximum residues (Tables 4.12.2.1. and 4.12.2.2). These results indicate that chlorpyrifos is the most frequently used pesticide by spray workers to control pests.
A reason for the presence of residues in blood serum is non-degradation of pesticides into their metabolites. The presence of pesticides residues in serum of spray workers is a matter of serious concern for public health, especially for pregnant females working in agricultural fields. Araoud et al. (2009) determined the multirsidues pesticides residues in human serum by GC-MS but in current study detection was carried out by most sensitive and reliable equipment HPLC. Modified procedures for detection of various pesticides from human biological samples were reported by Frias et al., (2001), Liu and Pleil (2002), Mathur et al. (2002), Russo et al. (2002), Schettgen et al. (2002), Heudorf et al. (2003), Ramesh and Ravi (2003) and Inoue et al. (2007). Pesticide residues in human serum and accumulation of pesticides residues in blood serum of female spray workers not only influenced their health but fetus also. 140
Subsequently residues transferred to the fetus by circulating blood of the mother as reported in previous studies (Safi, 2005; Elserougy et al., 2013).
In current study, for the identification of most OPs in the serum of agricultural spray workers, simple and rapid method was developed. This method is accurate and useful for the testing the pesticides in biological samples with the objective of management of poisoning due to pesticides. Pakistan is amongst the top ten world highest TB burden countries. The use of advanced molecular diagnostic techniques can help in determining a possibles upsurge of this disease related to exposure and susceptibility of people to factors such as pesticides as risk factors that can be conducive to the spread of TB. A rapid, reproducible, robust, inexpensive, and easy to use universal sample processing and diagnostic methodology applicable to any type of clinical specimen for the laboratory diagnosis of TB was developed in the present study. To the best of our knowledge, the present study reports the most sensitive method for detection of M. tuberculosis and M. bovis. In this study,M. tuberculosis and M. bovis were detected in both male as well as female spray workers by targeting histone like protein (hupB) gene, whereas in the control subjects no TB infection was detected by this molecular test. No mutation was detected in hupB gene. The strain found among all sprayers was predominently M. tuberculosis with very few incidences of M. bovis. Further, chi-square test indicated that there existed a significant different (P = 0.048) between positive M. tuberculosis and negative M. tuberculosis in female spray workers and also between positive M. bovis and negative M. bovis (P = 0.000) in female spray workers. .
Previously, no such study has been conducted in the District Gujranwala that provides adequate information about the effects of pesticides on hematological indices, such as liver function, lungs, and nerve enzymes of pesticidal spray workers. Even no previous study exists in the District on toxicity of pesticides and their health effects on exposed agricultural workers to these hazardous substances during work. In the District Gujranwala of Punjab, Pakistan, very little work has been conducted on pesticides toxicity and their effects on health of exposed workers to these hazardous substances during their routine work. Excessive use of toxic compounds can cause a variety of health hazards. These adverse effects multiply in the extremely poor prevailing conditions of health facilities in developing countries, such as Pakistan particularly in the rural areas. With this looming health threat, the present study was 141 undertaken to procure data regarding the issue and use the information for betterment of human health at large. Policy making and legal physical intervention authorities should take into consideration as to how to spread awareness about pesticide usage, their harmful health effects and mood consequences. Special programs addressing issues of field operators and handlers of pesticides should be launched including focusing on the urgency and importance of use of personal protection equipment, i.e. gloves, aprons, masks and goggles, etc. Additional programs aimed at minimizing or prevention of chemical hazards in agricultural environments should also be launched.
142
CONCLUSIONS
This study revealed that agricultural field workers exposed to pesticides contained residues of multiple pesticides in their blood serum analyzed by HPLC. Generally, the residues in blood may appear in low concentrations because as soon as a chemical pesticide enters into the human body, most of it is likely to be metabolized. Excessive exposure to pesticides results into accumulation of pesticides-caused cytotoxic changes. Results of the present study revealed organophosphates blood concentration and cholinesterase inhibition in spray workers. Increasing incidence of tuberculosis (M. tuberculosis and M. bovis) through molecular detection was documented in spray workers; toxic effects of pesticides may lead to a weak immune system and increased susceptibility to M. tuberculosis . The present work discoveredsome health risks associated with the occupational exposure to pesticides. It is recommended that regular molecular, biochemical and hematological checkups of pesticides-exposed agricultural field workers should be conducted to diagnose any early health problem at early stage. Further, over- exposure to pesticides should be avoided for occupational safety. In the District of Gujranwala, Punjab, Pakistan, the effect and extent of exposure of agricultural field workers to toxic synthetic chemicals documented in this study warrants further toxicological studies particularly with reference to agrochemicals and their metabolites. There also is a need to educate pesticides spray workers in terms of improvements of pesticides handling techniques and consequences of improper handling and abuses during field applications.
143
REFERENCES
Abu-Mourad, T. 2005. Adverse impact of insecticides on the health of Palestinian farm workers in the Gaza Strip: A hematologic biomarkers study. International Journal of occupational and Environmental Health, 11: 144-149. Abu-Qare, A. W. and Abou-Donia, M. B. 2001. Simultaneous determination of malathion, permethrin, DEET (N,N-diethyl-m-toluamide), and their metabolites in rat plasma and urine using high performance liquid chromatography. Journal of Pharmaceutical and Biomedical Analysis, 26(2): 291–299. Adad, L. M. D., de Andrade, H. H. R., Kvitko, K., Lehmann, M., Cavalcante, A. C. M. and Dihl, R. R. 2015. Occupational exposure of workers to pesticides: Toxicogenetics and susceptibility gene polymorphisms. Genetics and Molecular Biology, 38(3): 308-315. Adama, M. T., Ilboudo, S., Ouedraogo, M. and Guissou, I. P. 2012. Biological alterations and self-reported symptoms among insecticides-exposed workers in Burkina Faso. Interdisciplinary Toxicology, 5(1): 42–46. Ajayi, O. C. and Akinnifesi, F. K. 2008. Farmers' understanding of pesticide safety labels and field spraying practices: a case study of cotton farmers in northern Cote d'Ivoire. Science Research Essays, 2: 204-210. Aktar, M. W., Sengupta, D. and Chowdhury, A. 2009. Impact of pesticides use in agriculture, Their benefits and hazards. Interdisciplinary Toxicology, 2: 1–12. Alarcon, W. A., Calvert, G. M. and Blondell, J. M. 2005. Acute illnesses associated with pesticide exposures at schools. Journal of the American Medical Association, 294(4): 455-465. Alavanja, M. C., Sprince, N. L., Oliver, E., Whitten, P., Lynch, C. F., Gillette, P. P., Logsden-Sacket, N. and Zwerling, C. 2001. Nested case-control analysis of high pesticide exposure events from the Agricultural Health Study. American Journal of Industrial Medicine, 39: 557–563. Alpalan, G., Kanat, H. D., Dilek, B. and Altuntas, I. 2006. Effects of diazinon at different doses on rat liver and pancreas tissues. Pesticide biochemistry and physiology, 87: 103-108. Al-Sarar, A., Abo-Bakr, Y., Al-Erimah, G., Hussein, H. and Bayoumi, A. 2009. Hematological and biochemical alterations in occupationally pesticides-exposed workers of Riyadh municipality, Kingdom of Saudi Arabia. Research Journal of Environmental Toxicology, 3: 179-185. Amer, M. M., Metwalli, M. and Abu El-Magd, Y. 2002. Skin diseases and enzymatic antoxidant activity among workers exposed to pesticides. Eastern Mediterranean Health Journal, 8: 1- 9. Ani, A., Bruvik, T., Okoh, Y., Agaba, P., Agbaji, O., Idoko, J. and Dahle, U. R. 2009. Genetic diversity of Mycobacterium tuberculosis Complex in Jos, Nigeria. BMC Infectious Diseases, 10: 187-189. Antonio, F., Hernandeza, M., Amparo, G., Vidal, P., Jose, V., Garcıa, L., Gloria, P., Fernando, G., Olga, L., Lourdes, R., Guadalupe, P. and Antonio, P. 2006. Influence of exposure to pesticides on serum components and enzyme activities of cytotoxicity among intensive agriculture farmers. Environmental Research, 102(1): 70–76. 144
Aprea, C., Colosio, C., Mammone, T., Minola, C. and Maroni, M. 2002. Biological monitoring of pesticide exposure: a review of analytical methods. Journal of Chromatography, 769: 191–219. Aradhna and Singh, V. K. 2014. Haematological alterations in sprayers occupationally exposed to Multiple Pesticides. American-Eurasian Journal of Toxicological Sciences, 6(2): 35-38. Araoud, M., Douki, W., Najjar, M. F. and Kenani, A. 2010. Simple analytical method for determination of pesticide residues in human serum by liquid chromatography tandem mass spectrometry. Journal of Environmental Science Health, 45: 242-248. Araoud, M., Gazzah, N., Douki, W., Najjar, M. F. and Kenani, A. 2012. Rapid multi- residue method for the determination of pesticide residues in human serum. African Journal of Biotechnology, 11(62): 12579-12585. Arcury, T. A. and Quandt, S. A. 2007. Delivery of Health Services to Migrant and Seasonal Farmworkers. Annual Review of Public Health, 28: 345-363. Aroonvilairat, S., Kespichayawattana, W., Sornprachum, T., Chaisuriya, P., Siwadune, T. and Ratanabanangkoon, K. 2015. Effect of pesticide exposure on immunological, hematological and biochemical parameters in Thai Orchid Farmers, A cross-sectional study. International Journal of Environmental Research and Public Health, 12(6): 5846-5861. Athanasopoulos, P. E., Kyriakidis, N. V. and Stavropoulos, P. 2004. A study of the environmental degradation of pesticides azinphos methyl and parathion methyl. Journal of Environmental Science Health, 39 (2): 297-309. Atreya, K. 2008. Probabilistic assessment of acute health symptoms related to pesticide use under intensified Nepalese agriculture. International Journal of Environmental Health Research, 18 (3): 187-208. Awad, O. M., Fiki, S. A., Shanab, R. A., Hassanin, M. A. and Rahman, R. A. 2013. Influence of exposure to pesticides on liver enzymes and cholinesterase levels in male agriculture workers. Global Nest Journal, 16 (10): 20-21. Azmi, M. A., Naqvi, S. N. H., Azmi, M. A. and Aslam, M. 2006. Effect of pesticide residues on health and different enzyme levels in the blood of farm workers from Gadap (rural area) Karachi, Pakistan. Chemosphere, 64: 1739–44. Azmi, M. A., Naqvi, S. N., Akthar, K., Moinudddin, Parveen, S., Parveen, R. and Aslam, M. 2009. Effects of pesricides residues on health and blood parameters of farm workers from rural Gadap, Karachi, Pakistan. Journal of Environmental Biology, 30(5): 747-756. Baldi, I., Lebailly, P., Jean, S., Rougetet, L., Dulaurent, S. and Marquet, P. 2006. Pesticide contamination of workers in vineyards in France. Journal of Exposure Science and Environmental Epidemiology, 16: 115–124. Banica, F. G. 2012. Chemical Sensors and Biosensors: Fundamentals and Applications. 1st ed. John Wiley & Sons. Chichester, UK. pp. 575-576. Barr, D. B. and Needham, L. L. 2002. A nalytical methods for biological monitoring of exposure to pesticides: a review. Journal of Chromatography B, 778: 5–29. 145
Berthet, A., Hopf, N. B. Miles, A., Spring, P., Charrière, N., Garrigou, A., Baldi, I. and Vernez, D. 2014. Human skin in vitro permeation of bentazon and isoproturon formulations with or without protective clothing suit. Archive Toxicology, 88: 77–88. Bhalli, J. A., Khan, Q. M., Hag, M. A., Khalid, M. and Nasim, A. 2006. Cryptogenic analysis of Pakistani individuals occupationally exposed to pesticides in a pesticides production industry. Mutagenesis, 21: 143-148. Bhatia, A. S., Kumar, S. and Harinath, B. C. 2003. Immunodiagnosis of tuberculosis, an update. Indian Journal of Clinical Biochemistry, 18 (2): 1-5 Bhoopendra, S. and Dogra T. D. 2009. Rapid method for the determination of some organophosphorus insecticides in a small amount of serum in emergency and occupational toxicology cases. Indian Journal of Occupational and Environmental Medicine, 13(2): 84-87. Bolognesi, C. 2003. Genotoxicity of pesticides: a review of human biomonitoring studies. Mutation Research, 543: 251–272. Calvert, G. M. Plate D. K. Das, R. Rosales, R. Shafey, O. and Thomsen, C. 2004. Acute occupational pesticide-related illness in the U.S. 1998-1999: Surveillance findings form the SENSOR-pesticides Program. American Journal of Industrial Medicine, 45: 14-23. Cataudella, E., Malaguarnera, G., Gagliano, C., Condorelli, G., Antic, T., Liborio Rampello, L. Erdogan, O., Rampello, L., and Malaguarner, M. 2012. Pesticides exposure and the management of acute hepatic injurya. Acta Medica Mediterranea, 28: 245-247. Chadha, V. and Jagota, P. 2015. Challenges and strategies for control of tuberculosis among agricultural workers. National tuberculosis institute Bulletin, 38: 11-7. Chakravorty, S. and Tyagi, J. S. 2005. Novel multipurpose methodology for detection of mycobacteria in pulmonary and extrapulmonary specimens by smear microscopy, culture, and PCR. Journal of Clinical Microbiology, 43(6): 2697-2702. Chatzi, L., Alegakis, A., Tzanakis, N., Siafakas, N., Kogevinas, M. and Lionis, C. 2007. Association of allergic rhinitis with pesticide use among grape farmers in Crete, Greece. Occupational Environmental Medicine, 64: 417–421. Clark, L. C. and Lyons, C. 1962. Electrode systems for monitoring in cardiovascular surgery. Annual New York Academic Science, 102: 29-45. Clarke, M., Dick, J., Zwarenstein, M. and Diwan, V. 2003. DOTS for temporary workers in the agricultural sector. An exploratory study in tuberculosis case detection. Curationis, 26(4): 66-71. Colovic, M, B., Krstic, D. Z., Lazarevic-Pasti, T. D., Bondzic, A. M. and Vasic. V. M. 2013. Acetylcholinesterase inhibitors: pharmacology and toxicology. Current Neuropharmacology, 11(3): 315–335. Coronado, G. D., Thompson, B., Strong, L., Griffith, W. C. and Islas, I. 2004. Agricultural task and exposure to organophosphate pesticides among farmworkers. Environmental Health Perspective, 112: 142–147. Corsini, E., Liesivuori, J., Vergieva, T., Van Loveren, H. and Colosio, C. 2008. Effects of pesticide exposure on the human immune system. Human Exposure Toxicology, 27: 671–680. 146
Costa, L. G., Giordano, G., Cole, T. B., Marsillach, J. and Furlong, C. E. 2013. Paraoxonase 1 (PON1) as a genetic determinant of susceptibility to organophosphate toxicity. Toxicology, 307: 115-22. Cotton, J., Lewandowski, P. and Brumby, S. 2015. Cholinesterase research outreach project measuring cholinesterase activity and pesticide use in an agricultural community. BMC Public Health, 15: 748-750. Cruz, S., Lino, C. and Silveira, M. I. 2003. Evaluation of organochlorine pesticide residues in human serum from an urban and two rural populations in Portugal. Science Environment, 317: 23–35. Cunningham, S., Ruben, J. and Venkat-Narayan, K. 2008. Health of foreign-born people in the United States: A review. Health and Place, 14(4): 623–635. Curl, C. L., Fenske, R. A., Kissel, J. C., Shirai, J. H., Moate, T. F., Griffith, W., Coronado, G. and Thompson, B. 2002. Evaluation of take-home organophosphorus pesticide exposure among agricultural workers and their children. Environmental Health Perspective, 110(12): 787–792. Damalas, C. A. and Koutroubas, S. D. 2016. Farmers exposure to pesticides toxicity types and Ways of Prevention. Toxics, 4(1): 1-2. Dasgupta, S., Meisner, C., Wheeler, D., Xuyen, K. and Thi Lam, N. 2007. Pesticide poisoning of farm workers-implications of blood test results from Vietnam. International Journal of Hygiene and Environment Health, 210(2): 121-32. Del Prado-Lu, J. L. 2007. Pesticide exposure, risk factors and health problems among cutflower farmers: a cross sectional study. Journal of Occupational Medicine and Toxicology, 2: 9-16. Deshpande, D. S. and Srivastava, A. K. 2016. Method validation for simultaneous determination of pesticide residues in post-mortem samples by high performance liquid chromatography ultraviolet method. European Journal of Forensic Sciences, 3(3): 1-6. Dhalla, A. S. and Sharma, S. 2013. Assessment of Serum Cholinesterase in Rural Punjabi Sprayers Exposed to a Mixture of Pesticides. Toxicology International, 20(2): 154–159. Diaz-Resendiz, R. K. J., Toledo-Ibarra, G. A. and Giron-Perez M. I. 2015. Modulation of immune response by organophosphorus pesticides: fishes as a potential model in immunotoxicology. Journal of Immunology Research, 10: 1155-1165 Dulaurent, S., Saint-Marcoux, F., Marquet, P. and Lachtre, G. 2006. Simultaneous determination of six dialkylphosphates in urine by liquid chromatography tandem mass spectrometry. Journal of Chromatography B, 831: 223-229. Early, J., Davis, S. W., Quandt, S. A., Rao, P., Snively, B. M. and Arcury, T. A. Housing characteristics of farmworker families in North Carolina. Journal of Immigrant and Minority Health, 8(2): 173-184. Eddleston, M. 2000. Patterns and problems of deliberate self poisoning in the developing world. Advance internal medicine, 93: 715-731. Ejigu, D. and Mekonnen, Y. 2005. Pesticide use on agricultural fields and health problems in various activities. East African medical journal, 82: 427-435. 147
Elhalwagy, M. E. A. and Zaki N. I. 2009. Comparative study on pesticide mixture of organophosphorus and pyrethroid in commercial formulation. Environment Toxicology and Pharmacology, 28: 219-224. Ellman, G. L., Curtney, K. D. Andrews, V. and Featherstone, R. M. 1961. A new and rapid colorimetric determination of acetyl cholinesterase activity. Biochemical Pharmacology, 7: 88–95. Elserougy, S., Beshir, S., Saad-Hussein, A. and Abouarab, A. 2013. Organochlorine pesticide residues in biological compartments of healthy mothers. Toxicology and Industrial Health, 29(5): 441-448. Emam, S. J., Salehcheh, M. and Haghighizadeh, M. H. and Jazayeri, S. M. H. M. 2012. Occupational exposure to pesticides among farmers. Pakistan Journal of Medical Science, 28(1): 120-123. Farahat, T. M., Abdelrasoul, G. M., Amr, M. M., Shebl, M. M., Farahat, F. M. and Anger W. K. 2003. Neurobehavioural effects among workers occupationally exposed to organophosphorous pesticides. Occupational and Environmental Medicine, 60: 279–286. Fareed, M., Pathak, M. K., Bihari, V., Kamal, R., Srivastava, A. K. and Kesavachandran, C. N. 2013. Adverse respiratory health and hematological alterations among agricultural workers occupationally exposed to organophosphate pesticides: a cross-sectional study in North India. PloS one, 8(7): 1-10. Fareed, M., Pathak, M. K., Bihari, V., Mudiam, M. K. R., Patel, D. K. and Mathur, N. 2010. Hematological and biochemical alterations in sprayers occupationally exposed to mixture of pesticides at a mango plantation in Lucknow, India. Toxicological and Environ Chemistry, 92: 1919-1928. Faria, N. M., FacchiniII, L. A., Anaclaudia, G. F. and Tomasi, E. 2006. Farm work, dust exposure and respiratory symptoms among farmers. Revista de Saúde Pública, 40(5): 2-9. Franz, W., Mast, U., Kiderlen, D., Diepold, C. and Eyer, P. 1999. Improved determination of acetyl cholinesterase activity in human whole blood. Clinica Chimica Acta, 288(1): 73–90. Frias, M. M., Frenich, A. G., Martinez Vidal, J. L., Sanchez, M. M., Olea, F. and Olea, N. 2001. Analyses of lindane, vinclozolin, aldrin, p,p-DDE, o,p-DDT and p,p- DDT in human serum using gas chromatography with electron capture detection and tandem mass spectrometry. Journal of Chromatography B, 760: 1–15. Fukuyama, T., Tajima, Y., Ueda, H., Hayashi, K., Shutoh, Y., Harada, T. and Kosaka, T. 2009. Allergic reaction induced by dermal and/or respiratory exposure to low-dose phenoxyacetic acid, organophosphorus, and carbamate pesticides. Toxicology, 261: 152–161. Gamlin, J., Diaz, R. P. and Hesketh, T. 2007. Exposure of young children working on Mexican tobacco plantations to organophosphorous and carbamic pesticides, indicated by cholinesterase depression. Child Care Health and Development, 33(3): 246-248. Garcia-Garcia, C. R., Parron, T., Requena, M., Alarcon, R., Tsatsakis, A. M. and Hernande, A. F. 2016. Occupational pesticide exposure and adverse health effects at the clinical, hematological and biochemical level. Life Sciences, 145: 274–283. 148
George, L., Ellman, K., Courtney, D., Valentino, Andres, J. R. and Robert, M. F. 1961. A New and rapid colorimetric determination of acetylcholinesterase activity. Biochemical Pharmacology, 7(2): 91-95. Gertrudis, C., Mario, V., Arnaldo, V., Viviana, D., Isolde, R., Nicolas, H. and Gloria, C. 2001. A rat mammary tumor model induced by the organophosphorus pesticides parathion and Malathion, possibly through acetyl cholinesterase inhibition. Environmental Health Perspective, 109(5): 211-221. Hashmi, I. and Dilshad, K. A. 2011. Adverse Health Effects of Pesticides Exposure in Agricultural and Industrial Workers of Developing Country, the Impacts of Pesticides Exposure. Intech Publisher, Margarita Stoytcheva. pp. 155-178. Hayat, K., Ashfaq, M., Ashfaq, U. and Saleem, M. A. 2010. Determination of pesticide residues in blood samples of villagers involved in pesticide application at District Vehari (Punjab), Pakistan. African Journal of Environmental Science and Technology, 4(10): 666-684. Hernandez, A. F., Gomez, M. A., Pena, G., Gil, F., Rodrigo, L., Villanueva, E., and Pla, A., 2004. Effect of long-term exposure to pesticides on plasma esterases from plastic greenhouse workers. Journal of Toxicology and Environmental Health A, 67: 1095–1108. Hernandez, F. A., Gomez, M. A., Perez, V. G., Lario, V. J. and Pena, G. 2006. Influence of exposure to pesticides on serum components and enzymes activities of cytotoxicity among intensive agriculture farmers. Environment Research, 102: 70-76. Heudorf, U., Angerer, J. and Drexler, H. 2003. Current internal exposure to pesticides in children and adolescents in Germany: blood plasma levels of pentachlorophenol (PCP), lindane (γ -HCH), and dichloro(Diphenyl)ethylene (DDE), a biostable metabolite of dichloro(diphenyl) trichloroethane (DDT). International Journal of Hygiene and Environment Health, 206: 485-512. Hoppin, J. A., David, M., Umbach, S., London, J., Michael, C. R., Alavanja, D. P. and Sandler, J. A. 2002. Chemical predictors of wheeze among farm pesticides applicators in the agriculture health study. American Journal of Respiratory and Critical Care Medicine, 165: 683-689. Hoppin, J. A., London, S. J., Lynch, C. F., Alavanja, M. C. and Sandler, D. P. 2006. Pesticides associated with wheeze among commercial pesticide applicators in the Agricultural Health Study. American Journal of Epidemiology, 163(12):1129-1137. Hossain, S. M. Z., Luckham, R. E., McFadden, M. J. and Brennan, J. D. 2009. Reagentless bidirectional lateral flow bioactive paper sensors for detection of pesticides in beverage and food samples. Analytical Chemistry, 81: 9055–9064. Hurtig, A. K., Sebastian, M. S., Soto, A., Shingre, A., Zambrano, D. and Guerrero, W. 2003. Pesticide use among farmers in the Amazon Basin of Ecuador. Archive Environmental Health, 14 (58): 223-228. Ibrahim, K. S., Amer, N. M., El-Tahlawy, E. M. and Abd Allah H. M. 2011. Reporoductive outcome, hormone levels and liver enzymes in agricultural female workers. Journal of Advanced Research, 2: 185-189. Inoue, S., Saito, T., Mase, H., Suzuki, Y., Takazawa, K., Yamamoto, I. and Inokuchi, S. 2007. Rapid simultaneous determination for organophosphorus pesticides in human serum by LC-MS. Journal of Pharmacology and Biomedical Analas, 44: 258-64. 149
Ismail, A., Rohlman, D., Rasoul, G. A., Salem, M. A. and Hendy, O. 2010. Clinical and biochemical parameters of children and adolescents applying pesticides. The international journal of occupational and environmental medicine, 1: 132–143. Itoh, H., Kawasaki, S. and Tadano, J. 1996. Application of liquid- chromatography/mass spectrometry to pesticide analysis. Journal of Chromatgraphy, 754: 61-76. Jaga, K. and Dharmani, C. 2003. Sources of exposure to and public health implications of organophosphate pesticides. Panam Journal of Public Health, 14(3): 171- 172. Jamal, F. and Quazi S. Haque, Q. S. and Lohia, M. R. 2016. The reproductive health and liver functions of occupationally exposed female pesticide sprayers of mango plantations. Journal of Clinical Toxicology, 6:1-2. Jamil, K., Das, G. P., Shaik, A. P., Dharmi, S. and Murthy, S. 2007. Epidemiological studies of pesticides exposed individuals and their clinical implications. Current Science, 92:340-345. Jana, S., Labenia, J. S., Baldwin, D. H., French, B. L., Davis, J. W. and Scholz, N. L. 2007. Behavioral impairment and increased predation mortality in cutthroat trout exposed to carbaryl. Marine Ecology Progress Series, 329: 1–11. Jennifer, E. K., Jonathan, N. H., Theresa, R. S., Cunningham, R. N., Richard, A. F., Christopher, D. S. and Matthew, K. 2014. Determinants of butyrylcholinesterase inhibition among agricultural pesticide handlers in Washington State. Annals Occupational Hygiene, 59(1): 25–40. Jindal, T., Singh, D. K. and Agarwal, H. C. 2007. Effect of UV radiation and temperature on mineralization and volatilization of coumaphos in water. Journal of Environmental Science Health, 42: 367–372. Jokanovic, M. and Prostran, M. 2009. Pyridinium oximes as cholinesterase reactivators. Structure activity relationship and efficacy in the treatment of poisoning with organophosphorus compounds. Current Medicine Chemistry, 16: 2177-2188. Jors, E., Morant, R. E., Aguilar, G. C., Huici, L. F., Baelum, J. and Konradsen, F. 2006. Occupational pesticides intoxications among farmers in Bolivia a cross- sectional study. Environment Health Global Science, 5: 1-9. Joshaghani, H. R., Ahmadi, A. R. and Mansourian, A. R. 2007. Effects of occupational exposure in pesticide plant on workers' serum and erythrocyte cholinesterase activity. International Journal of Occupational Medicine and Environmental Health, 20(4): 381-385. Jyotsna, A. P., Arun, J. P. and Sanjay, P. 2003. Biochemical effects of various pesticides on sprayers of Grape garden. Indian Journal of Biochemistry, 21: 16-22. Kamel, F. and Hoppin, J. A. 2004. Association of pesticide exposure with neurologic dysfunction and disease. Environmental Health Perspective, 112: 950-958. Karabay, N. U., Cakmak, B., Saym, F. and Oguz, M. G. 2004. Risk assessment of organophosphate pesticide exposure on greenhouse workers in Menderes Region, Develi Village (Turkey). Turkiye Klinikleri Journal of Medical Sciences, 24: 6-11. Kasiotis, K. M., Souki, H., Tsakirakis, A. N., Carageorgiou, H., Theotokatos, S. A., Haroutounian, S. A. and Machera, K. 2008. Headspace solid phase micro extraction 150 gas chromatographic determination of fenthion in human serum. International Journal of Molecular Science, 9: 906–913. Kedia, S. K. and Palis, F. G. 2008. Health effects of pesticide exposure among filipino rice farmers. The Applied Anthropologist, 28(1): 40-51. Kesovachandran, C. N., Rastogi, S. K., Mathur, N., Siddiqui, M. K. J., Singh, V. K., Biharivipin and Bhasti, R. S. 2006. Health status among pesticide applicators at a Mango plantation in India. Journal of Pest Safety, 8: 1-8. Khan, A. A., Shah, M. A., and Rahman, S. 2013. Occupational exposure to pesticides and its effects on health status of workers in Swat, Khyber Pakhtunkhwa, Pakistan. Journal of Biological Life Sciences, 4(2): 43-55. Khan, A. D., Bhatti, M. M., Khan, F. A., Naqvi, S. T. and Karam, A. 2008. Adverse effects of pesticides residues on biochemical markers in Pakistani tobacco farmers. International Journal of Clinical and Experimental Medicine, 1: 274-282. Khan, K. H. 2012. Impact of endosulfan on living beings. International Journal of Bioscience. 2:9–17. Khan, M. F., Khan, M. I., Aslam, M. and Naqvi, S.N.H. 2000. Study of cholinesterase level in blood of cotton field workers exposed to pesticides. Journal of Baqai Medical University, 3: 12 -16. Kim, T. S., Kim, J. K., Choi, K., Stenstrom, M. K. and Zoh, K. D. 2006. Degradation mechanism and the toxicity assessment in TiO2 photocatalysis and photolysis of parathion. Chemosphere, 62: 926–933. Konradsen, F., Hoek, W., Cole, D. C., Hutchinson, G., Daisley, H., Singh, S. and Eddleston, M. 2003. Reducing acute poisoning in developing countries-options for restricting the availability of pesticides. Toxicology, 192: 249-261. Lacassie, E., Marquet, P., Gaulier, J., Dreyfuss, M. and Lachatre, G. 2001. Sensitive and specific multiresidue methods for the determination of pesticides of various classes in clinical and forensic toxicology. Forensic science international, 121(2): 116–125. Lacassie, E., Dreyfuss, J. M., Gaulier, F. M., Marquet, P. Daguet, J. L. and Lachatre, G. 2001. Multiresidue determination method for organophosphorus pesticides in serum and whole blood by gas chromatography mass-selective detection. Journal of Chromatography B and Biomedical Sciences and Application, 759(1): 109-116. Ladou, 2004. Current occupational and environmental medicine, 4th ed. Lange medical books McGraw- Hill..USA. pp. 391-405. Lai, M. W., Schwartz, W., Rodgers, G. C., Abramsky, L., Haber, D. A. and Bronstein, A. C. 2005. Annual report of the American association of poison control Centers' national poisoning and exposure database. Journal of Toxicology and Clinical Toxicology, 44: 803-932. Latif, Y., Sherazi, T. H., Bhanger, M. I. and Nizamani, S. 2012. Evaluation of pesticide residues in human blood samples of agro professionals and non-agro professionals. American Journal of Analytical Chemistry, 3: 587-595. Lebaillt, P. A., Devaux, D., Pottie, M. and Baldi, I. 2003. Urine mutagenicity and lymphocyte DNA damage in fruit growers occupationally exposed to fungicide captan. Occupational and Environmental Medicine, 60: 910-917. 151
Lebailly, P., Bouchart, V., Baldi, I., Lecluse, Y., Heutte, N., Gislard, A. and Malas, J. P. 2008. Exposure to pesticides in open-field farming in France. The Annals of Occupational Hygiene, 53(1): 69-81. Lee, W. J., Cha, E. S. and Moon, E. K. 2010. Disease prevalence and mortality among agricultural workers in Korea. Journal of Korean Medical Science, 25: 112- 118. Leilanie, J. and Delprado, L. 2007. Pesticide exposure, risk factors and health problems among cutflower farmers: a cross sectional study. Journal of Occupational Medicine and Toxicology, 2: 1-9. Liu, S. and Pleil, J. D. 2002. Human blood and environmental media screening method for pesticides and polychlorinated biphenyl compounds using liquid extraction and gas chromatography-mass spectrometry analysis. Journal of Chromatography B, 769: 155-167. Mahmood, F., Khan, A., Riaz, H. R. and Khan, I. A. 2014. Molecular based epidemiology of bovine pulmonary tuberculosis a Mortal Foe. Pakistan Veterinary Journal, 34(2): 185-188. Mason, H. J. 2000. The recovery of plasma cholinesterase and erythrocyte acetylcholinesterase activity in workers after over-exposure to dichlorvos. Occupational Medicine, 50: 343–347. Mathur, V., Bhatnagar, P., Sharma, R. G., Acharya, V. and Sexana, R. 2002. Breast cancer incidence and exposure to pesticides among women originating from Jaipur. Environmental International, 28: 331-336. Mekonnen, Y and Ejigu, D. 2005. Plasma cholinesterase level of Ethiopian farm workers exposed to chemical pesticide. Occupational Medicine, 55: 504–505. Misra, U.K., Prasad M. and Pandey C. M. 1994. A study of coganitive functions and event related potentials following organophosphate exposure. Electromyography and clinical neurophysiology, 34(4): 197-203. Mnif, W., Hassine, A. I. H., Bouaziz, A., Bartegi, A., Thomas, O. and Roig B. 2011. Effect of endocrine disruptor pesticides. A Review: International Journal of Environmental Research and Public Health, 8: 2265-2303. Mokrousov, I., Otten, T., Filipenko, M., Vyazovaya, A., Chrapov, E., Limeschenko, E., Steklova, L., Vyshnevskiy, B. and Narvskaya, O. 2002. Detection of isoniazid- resistance Mycobacterium tuberculosis strains by a Multiplex Allele-Specific PCR assay targeting katG codon 315 variation. Journal of Clinical Microbiology, 40(7): 2509-2512. More, P. R., Vadlamudi, V. P., Degloorkar, N. M. and Rajurkar, S. R. 2003. Health monitoring of farm labourers engaged in MIPC 50 WP field sprays. Journal of Environmental Biology, 24: 205–209. Mosudi, B., Sosan, A. E., Akingbohungbe, Isaac, A. O. and Muheez, A. D. 2008. Insecticide residues in the blood serum and domestic water source of cacao farmers in Southwestern Nigeria. Chemosphere, 72(5): 781-784. Muddasir, B., Dhar, J. K., Shafiqa, A., Sabia, Q., Tariq, J. and Bhavna, G. 2010. Pesticide residues in blood serum samples from inhabitants of Dal Lake hamlets in 152
Jammu & Kashmir, India (2008-2010). Journal of Environmental Science, Toxicology and Food Technology, 1 (2): 26-31. Mukund, U. and Sheela, R. 1996. Tackling rB - the search for solutions; the foundation for research in a community health. Health Administrator, 15: 72-79. Mulchandani, A., Mulchandani, P., Kaneva, I. and Chen, W. 1998. Biosensor for direct determination of organophosphate nerve agents using recombinant Escherichia coli with surface-expressed organophosphorus hydrolase, Potentiometric microbial electrode. Analytical Chemistry, 70 (19): 4140-4145. Murphy, H. H., Hoan, N. P., Matteson, P., Linda, A. C. and Abubakar, M. 2002. Farmers self-surveillance of pesticide poisoning: A 12-month pilot study in Northern Vietnam. International Journal of Occupational and Environmental Health, 8(3): 202-203. Nagatani, N., Takeuchi, A., Hossain, M. A., Yuhi, T., Endo, T. and Kerman, K. 2007. Rapid and sensitive visual detection of residual pesticides in food using acetylcholinesterase-based disposable membrane chips. Food Control. 18: 914–920. Naidoo, S., London, L., Burdorf, A., Naidoo, R. N. and Kromhout, H. 2008. Agricultural activities, pesticide use and occupational hazards among women working in small-scale farming in northern KwaZulu-Natal, South Africa. International journal of environmental health, 14: 218-224. Negi, S. S., Khan, S. F. B. and Gupta, S. 2005. Comparison of the conventional diagnostic modalities, BACTEC culture and polymerase chain reaction test for diagnosis of tuberculosis. Indian Journal of Medical Microbiology, 23(1): 29-33. Nerilo, S. B., Martins, F. A., Nerilo, L. B., Salvadego, V. E. C., Endo, R. Y. and Junior, M. M. 2014. Pesticide use and cholinesterase inhibition in small-scale agricultural workers in southern Brazil. Brazilian Journal of Pharmaceutical Science, 50: 783–791. Neupane, D., Jors, E. and Lars Brandt, L. 2014. Pesticide use, erythrocyte acetylcholinesterase level and self-reported acute intoxication symptoms among vegetable farmers in Nepal: a cross-sectional study. Environmental Health, 13: 98-99. Niemann, S., Richter, E. and Gerdes, S. R. 2000. Differentiation among members of the Mycobacterium tuberculosis complex by molecular and biochemical features: evidence for two pyrazinamide-susceptible subtypes of M. bovis. Journal of Clinical Microbiology, 38: 152–157. Ofukwu, R. A., Oboegbulem, S. I. and Akwuobu, C. A. 2008. Zoonotic Mycobacterium species in fresh cow milk and fresh skimmed, unpasteurised market milk (nono) in Makurdi, Nigeria: implications for public health. Journal of Animal Plant Science, 1(1): 21-25. Ohayo-Mitoko, G. J., Kromhout, H., Simwa, J. M., Boleij, J. S. and Heederik, D. 2000. Self-reported symptoms and inhibition of acetylcholinesterase activity among Kenyan agricultural workers. Occupational and Environmental Medicine, 57: 195– 200. Olga, L., Antonio, F., Hernandez, Lourdes, R., Fernando, G., Gloria, P., Jose, L., Serrano, T., Parron , E. V. and Antonio, P. 2007. Changes in antioxidant enzymes in humans with longterm exposure to pesticide. Toxicology Letters, 171: 146–153. 153
Panda, S and Nanda, R. 2011. Serum creatine phosphokinase, a probable marker of severity in organophosphorus poisoning. Toxicolgy International, 18: 117-123. Parron, T., Requena, M., Hernandez, A. F. and Alarcon, R. 2014. Environmental exposure to pesticides and cancer risk in multiple human organ systems. Toxicology Letter, 230(2): 157-165. Pastor, S. L., Lucero, L., Gutierrez, Z. and Parron T. 2002. Follow up study on micronucleus frequency in spanish spray workers exposed to pesticides. Mutagenesis, 17: 79-82. Patel, P. D. 2002. Biosensors for measurement of analytes implicatedin food safety. Trends Analytical Chemistry, 21: 96-115. Pathak, M. K., Fareed, M., Bihari, V., Reddy, M. M. Patel, D. K, 2011. Cholinesterase levels and morbidity in pesticide sprayers in North India. Occupational Medicine, 61(7): 512–514. Patil, J. A., Patil, A. J., Sontakke, A. V. and Govindwar, S. P. 2009. Occupational pesticides exposure of sprayers of grape gardens of Western Maharashtra (India): effects on liver and kidney implications. Journal of basic Physiology and Pharmacology, 20(4): 335-355. Patil, J., Patil, A. J. and Govindwar, S. P. 2003. Biochemical effects of various pesticides on sprayers of grape gardens. Indian Journal of Clinical Biochemistry, 18: 16-22. Payan-Renteria, R., Garibay-Chavez, G., Rangel-Ascencio, R., Preciado-Martínez, V., Muñoz-Islas, L. and Beltran-Miranda, C. 2012. Effect of chronic pesticide exposure in farm workers of a Mexico community. Archives of environmental and occupational health, 67: 22-30. Pimentel, D., Zuniga, R. and Morrison, D. 2005. Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecological Economics, 52: 273 – 288. Pitarch, E., Lopez, F. J., Serrano, R. and Hernandez, F. 2001. Multiresidue determination of organophosphorus and organochlorine pesticides in human biological fluids by capillary gas chromatography. Fresenius Journal of Analytical Chemistry, 369: 502–509. Prabhakar, S., Mishra, A., Singhal, A., Katoch, V.M., Thakral, S. S., Tyagi, J. S. and Prasad, H. K., 2004. Use of the hupB gene encoding a histone like protein of Mycobacterium tuberculosis as a target for detection and differentiation of M.tuberculosis and M.bovis. Journal of Clinical Microbiology, 42(6): 2724-32. Radon, K., Monso, E., Weber, C., Danuser, B., Iversen, M. and Opravil, U. 2002. Prevalence and risk factors for airway diseases in farmers. Annals of Agricultural and Environmental Medicine, 9(2): 207-213. Ramesh, A. and Ravi, P. E. 2003. Determination of residues of endosulfan in human blood by a negative ion chemical ionization gas chromatographic/mass spectrometric method: impact of long-term aerial spray exposure. Pest Management Science, 59: 252-258. Rastogi, S. K., Singh, V. K., Kesavachandran, C., Jyoti, M. K., Siddiqui, J., Mathur, N. and Bharti R. S. 2008. Monitoring of plasma butyrylcholinesterase activity 154 and hematological parameters in pesticide sprayers. Indian Journal of Occupational and Environmental Medicine, 12(1): 29–32. Remor, A. P., Totti, C. C., Moreira, D. A., Dutra, G. P., Heuser, V. D. and Boeira, J. M. 2009. Occupational exposure of farm workers to pesticides, biochemical parameters and evaluation of genotoxicity. Environment International, 35: 273-278. Richard, S. G., Burgos, J. L., Lainz, A. R., Brodine, S., Pietrucha, A., Rondinelli, A., Rafael Laniadolaborin, R., Ibarra, E., Canez, A. and Fraga, M. 2011. Latent tuberculosis infection in a migrant agricultural community in Baja California, Mexico. Journal of Immigrant Minorty Health, 13(5): 940–947. Rigotto, R. M., Vasconcelos, D. P. and Rocha, M. M. 2014. Pesticide use in Brazil and problems for public health. Cadernos de Saude Publica, 30: 1360-1362. Rivero, A., Marquez, M., Santos, J., Pinedo, A., Sanchez, M. A., Esteve, A., Samper, S and Martin, C. 2001. High Rate of Tuberculosis Reinfection during a Nosocomial Outbreak of Multidrug-Resistant Tuberculosis Caused by Mycobacterium bovis Strain B. Clinical Infectious Diseases, 32(1): 159-161. Roberts, D. M., Fraser, J. F., Buckley, N. A. and Venkatesh, B. 2005. Experiences of anticholinesterase pesticide poisonings in an Australian tertiary hospital. Anaesthesia and intensive care, 33: 469-476. Roldan, T. L., Nieto, F. A., Aguilla, E. M., Laynez, F. and Parron T. 2006. Neurophysiologial sequela from acute poisoning and long term exposure to carbamate and organophosphate pesticides. Neurotoxicology and Teratology, 28: 694–703. Russo, M. V., Campanella, L. and Avino, P. 2002. Determination of organophosphorus pesticide residues in human tissues by capillary gas chromatography-negative chemical ionization mass spectrometry analysis. Journal of Chromatography B, 780: 431-441. Safi, J., Mourad, T. A. and Yassin, M. 2005. Hematological biomarkers in farm workers exposed to organophosphorus pesticides in the Gaza Strip. Archives of environmental and occupational health, 60: 235-241. Salameh, R. P., Daldi, I., Brochard, P. and Saleh, B. A. 2004. Pesticides in Lebanon: a knowledge, attitude and practise study. Environment Research, 94: 1-6. Sarwar, M. 2015. The dangers of pesticides associated with public health and preventing of the risks. International Journal of Bioinformatics and Biomedical Engineering, 1: 130–136. Saxena, P. and Saxena, A. K. 2010. Cypermethrin induced biochemical alterations in the blood of albino rats. Jordan Journal of Biological Sciences, 3: 111-114. Schettgen, T., Koch, H. M., Drexler, H. and Angerer, J. 2002. New gas chromatographic-mass spectrometric method for the determination of urinary pyrethroid metabolites in environmental medicine. Journal of Chromatography B, 778: 121-130. Schulze, H., Scherbaum, E., Anastassiades, M., Vorvola, S., Schmid, R. D., Bachmann, T. T., 2002a. Development, validation, and application of an acetylcholinesterase-biosensor test for the direct detection of insecticide residues in infant food. Biosensor Bioelectronics, 17: 1095- 1105. 155
Schulze, H., Schmid, R. D., Bachmann, T. T. 2002b. Rapid detection of neurotoxic insecticides in food using disposable acetylcholinesterase-biosensors and simple solvent extraction. Analytical and Bioanalytical Chemistry. 372: 268-272. Senthil, N. R., Ranjani, M. R. and Vasumath, K. 2014. Comparative diagnosis of Mycobacterium bovis by polymerase chain reaction and Ziel- Neilson staining technique using milk and nasal washing. Journal of Research in Agriculture and Animal Science, 2 (5): 1-3. Shinnawy, M. S. 2008. Effects of orally fed diazinon on some biochemical parameters of male albino rats. The Egyptian Journal of Hospital Medicine, 33: 559– 568. Singh, K. K., Muralidhar, M., Kumar, A., Chattpoadhyaya, T. K., Kapila, K., Singh, M. K., Jain, N. K. and Tyagi, J. S. 2000. Comparison of in house polymerase chain reaction with conventional techniques for the detection of Mycobacterium tuberculosis DNA in granulomatous lymphadenopathy. Journal of Clinical Pathology, 53: 355–361. Singh, S., Kumar, V., Thakur, S., Banerjee, B. D., Chandna, S., Rautela, S. R., Grover, S. S. Rawat, D. S., Pasha, S. T. Jain, S. K., LalIchhpujani, R. and Arvind, R. 2011. DNA damage and cholinesterase activity in occupational workers exposed to pesticides. Environmental toxicology and pharmacology, 31: 278–285. Singh, S., Saluja, T. P., Kaur, M. and Khilnani, G. C. 2008. Comparitive evaluation of FASTplaque assay with PCR and other conventional methods for the early detection of pulmonary tuberculosis. Journal of Clinical Laboratory Analysis, 22(5): 367-74. Skrzypczak, L. K., Cyranka, M., Skrzypczak, M. and Kruszewski, M. 2011. Biomonitoring and biomarkers of organophosphate pesticides exposure state of the art. Annals of Agricultural and Environmental Medicine, 18(2): 294-303. Smit, L. A. Wandel B. N. and Heedrik, D. 2003. Neurological symptoms among Srilankan farmers occupationally exposed to acetylcholinesterase- inhibiting insecticides. American Journal of Industrial Medicine, 44: 254-64. Soogarun, S., Wiwanitkit, V. and Suwansaksri, J. 2003. Report on blood cholinesterase among vegetable growers. The Southeast Asian Journal of Tropical Medicine and Public Health, 34(3): 687-689. Soomro, A. M., Seehar, G. M., Bhanger, M. I. and Channa, N. A. 2008. Pesticides in the blood samples of spray-workers at agriculture environment, the toxicological evaluation. Pakistan Journal of Anal Environmental Chemistry, 9(1): 32 -37. Steerenberg, P., Amelsvoort, L., Colosio, C., Corsini, E., Fustinoni, S., Vergieva, T., Zaikov, C., Pennanen, S., Liesivuori, J. and Loveren, H. 2008. Toxicological evaluation of the immune function of pesticide workers: A European wide assessment. Human Exposure Toxicology, 27: 701–707. Storm, J. E., Rozman, K. K. and Doull, J. 2000. Occupational exposure limits for 30 organophosphate pesticides based on inhibition of red blood cell acetylcholinesterase. Toxicology, 150: 1–29. Strong, L. L., Thompson, B., Coronado, G. D., Griffith, W. C., Vigoren, E. M. and Islas, I. 2004. Health symptoms and exposure to organophosphate pesticides in farmworkers. American Journal Industrial Medicine, 46: 599–606. 156
Sukonthamana, P., Temphattharachok, P., Thammasanya, W., Kraichart, T. and Tientavorn, T. 2015. Factors associated with pesticides used and plasma cholinesterase level among agricultural workers in rural area, Thailand. International Journal of Environmental and Ecological Engineering, 52(1): 89-98. Tarbah, A. F., Hellmutt, M., Oliver, T. and Thomas, D. 2001. An analytical method for the rapid screening of organophosphate pesticides in human biological samples and foodstuffs. Forensic Science Internships, 121: 126-133. Tariq, M. I. Afzal, S. Hussain, I. and Sultana, N. 2007. Pesticide exposure in Pakistan: A review. Environmental International, 33: 1107-1108. Thapa, B. R. and Anuj, W. 2007. Liver function test and their interpretation. Indian Journal of Pediatrics, 74(7): 663-667. Thevenot, D. R., Toth, K., Durst, R. A. and Wilson, G. S. 2001. Electrotecnical biosensors: recommended definitions and classification. Biosensor Bioelectronics, 16: 121-131. Tilak, K. S. and Sravanthi, M. 2014. Studies on biochemical changes of acetyl and butryl cholinesterases in the sprayers exposed to organophoshorous pesticides in Nuziveedu Krishna District A.P., India. Global Journal of Science Frontier Research, 14 (4): 1-8. Tokorska, M., Luty, S. T. and Haratym, M. 2004. Selected parameters of immunological response in hop growers during the period of intensive application of pesticides. Annals of Agricultural and Environmental Medicine, 11: 227-231. Trojanowicz, M. 2002. Determination of pesticides using electrochemical enzymatic biosensors. Electroanalysis, 14: 1311-1328. Tsoukali, H., Theodoridis, G., Raiko, N. and Grigoratou, I. 2005. Solid phase microextraction gas chromatographic analysis of organophosphorus pesticides in biological samples. Journal of Chromatography B, 822: 194–200. Ullah, S., Ahmed, M. M., Maqsood, A. and Rehman, O. 2008. Agricultural survey of Gujranwala, exploring district rural economy. 1: 8-12. Undeger, U. and Basaran, N. 2001. Effects of pesticide exposure on serum immunoglobulin and complement levels. Immunopharmacology Immunotoxicology, 23: 437–443. Venkataramana, G. and Sankararaman, S. 2005. Synthesis, absorption, and fluorescence emission properties of 1,3,6,8-Tetraethynylpyrene and its derivatives. European Journal of Organic Chemistry, 19: 4162-4166. Wang, J., McIntosh, F., Radomski, N., Dewar, K., Simeone, R., Enninga, J., Brosch, R, Rocha, E. P., Veyrier, F. J. and Behr, M. A. 2015. Insights on the emergence of Mycobacterium tuberculosis from the analysis of Mycobacterium kansasii. Genome Biology and Evolution, 7(3): 856-870. Weigel, M. M., Armijos, R. X., Hall, Y. P., Ramirez, Y. and Orozco, R. 2007. The household food insecurity and health outcomes of U.S–Mexico border migrant and seasonal farmworkers. Journal of Immigrant and Minority Health, 9: 157-169. Weiyue, Q. U., Rominder, P. S. S., Xinhui, B. I., Sheng, G. and Jiamo, F. 2010. Exposure of young mothers and newborns to organochlorine pesticides (OCPs) in Guangzhou, China. Science Total Environment, 408: 3133–3138. 157
Wesseling, C. Aragon, A. Castillo, L. Corriols, M. Chaverri, F. Cruz, E. Keifer, M. Monge, P. Partanen, T. J. Ruepert, C. Wendel, and Joode, B. 2001. Hazardous pesticides in Central America. International Journal of Occupational and Environmental Health, 7: 287-294. Wesseling, C., Keifer, M., Ahlbom, A., McConnell, R., Moon, J. and Rosenstock, L. 2002. Long-term neurobehavioral effects of mild poisonings with organophosphate and n-methyl carbamate pesticides among banana workers. International Journal of Occupational and Environmental Health, 8: 27–34. Wesseling, C., McConnell, R., Partanen, T. and Hogstedt, C. 1997. Agricultural pesticide use in developing countries: health effects and research needs. International Journal of Health Services, 27: 273-308. Wilson, C. and Tisdell, C. 2001. Why farmers continue to use pesticides despite environmental, health and sustainability costs. Ecological Economics, 39: 449–462. WMA, 2008. World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. Seoul. pp. 1-3. www.googlemap.com Yang, Z. T., Durmaz, R., Yang, D., Gunal, S., Zhang, L., Foxman, B., Sanic, A. and Marrs, C.F., 2005. Simultaneous detection of Isoniazid, rifampinn and ethambutol resistance of mycobacterium tuberculosis by single mutiplex allele specific polymerase chain reaction (PCR) assay. Diagnostic Microbiology and Infectious Diseases, 53(3): 201-208. Yassin, M. M. AbuMourad, T. A. Safi, J. M. 2002. Knowledge, attitude, practice, and toxicity symptoms associated with pesticide use among farm workers in the Gaza Strip. Occupational and Environmental Medicine, 59: 387-393. Yassin, M. M. 2003. Biological parameters of organophosphorus pesticides sprayers in the Gaza Strip. Egyptian Journal of Forensic Science and Applied Toxicology, 3: 11-21. Yousaf, M. I., Demerdash, K. I., Kamel, W. C. and Salhen, K. S. 2003. Changes in some hematological and biochemical indices of rabbits induced by isoflavones and cypermethrin. Toxicology, 189: 223-234.
x
ANNEXURES Annexure (I) Location of Study Area Geographical Coordinates District Gujranwala
Serial Village Latitude Longitude 1. Dharam Kot-Nawan 32° 16' 56" 73° 52' 44" Kot 2. Pindori 32° 18' 03" 73° 52' 40" 3. New Pindori 32° 18' 46" 73° 53' 08" 4. Ajit Kay Chattha 32° 17' 21" 73° 53' 56" 5. Shair Pur 32° 16' 47" 73° 54' 11" 6. Jam Wala 32° 17' 40" 73° 55' 31" 7. Jugna 32° 17' 52" 73° 56' 37" 8. Mohulanke 32° 16' 37" 73° 57' 27" 9. Kliary 32° 15' 25" 73° 56' 38" 10. Dhelha Chattha 32° 14' 54" 73° 58' 14" 11. Maryam Abad 32° 15' 07" 73° 56' 24" 12. Varpal Chattha 32° 15' 09" 73° 54' 15" 13. Boraywal Hanjra 32° 14' 36" 73° 55' 58" 14. Saharan Chattha 32° 13' 41" 73° 53' 37" 15. Kot Rasolpuryan 32° 13' 27" 73° 54' 35" 16. Dera Chattha 32° 12' 36" 73° 54' 50" 17. Kot Fazala 32° 12' 20" 73° 52' 43" 18. Wazirke Chattha 32° 11' 34" 73° 54' 07" 19. Nadala 32° 11' 46" 73° 55' 58" 20. Dargahi Wala 32° 11' 19" 73° 56' 51" 21. Dapai Mahatab Singh 32° 11' 02" 73° 55' 21" 22. Tapai Wasaka Singh 32° 10' 20" 73° 56' 24" 23. Tari Wala 32° 10' 13" 73° 55' 09" 24. Nai Wala 32° 10' 19" 73° 53' 31" 25. Noian Wala 32° 10' 38" 73° 52' 38" 26. Madan Chak 32° 09' 39" 73° 51' 09" 27. Kot Kalian 32° 10' 29" 73° 49' 31" 28. Jhatan Wali 32° 10' 04" 73° 48' 16" 29. Jhatanwala Sharqi 32° 09' 40" 73° 48' 48" 30. Harchoke 32° 08' 54" 73° 49' 25" 31. Gajar Gola Village 32° 12' 11" 73° 45' 22" 32. Sooian Wala 32° 14' 54" 73° 41' 57" 33. Barubgarh 32° 19' 23" 73° 43' 43" 34. Nai Wala Chattha 32° 11' 22" 73° 50' 33" 35. Ali Kot 32° 12' 34" 73° 50' 16" 36. Gandian Wali 32° 12' 22" 73° 48' 54" 37. Bucha Chattha 32° 13' 18" 73° 50' 10" 38. Sadhan Wali 32° 14' 10" 73° 47' 50" 39. Fateh Pur 32° 14' 42" 73° 49' 47" 40. Said Nagar 32° 14' 54" 73° 47' 46" 41. Ali Pur Chattha 32° 16' 03" 73° 48' 54"
xi
42. Sarwala Village 32° 16' 35" 73° 47' 24" 43. Kailiyan Wala 32° 17' 03" 73° 45' 19" 44. Kot Hara 32° 16' 45" 73° 42' 48" 45. Madrassah Chattha 32° 15' 56" 73° 43' 12" 46. Rasool Nagar 32° 19' 37" 73° 46' 48" 47. Hussain Pur 32° 18' 33" 73° 47' 50" 48. Bhaghy Da Kot 32° 17' 51" 73° 49' 12" 49. Rasool Pur 32° 18' 06" 73° 47' 29" 50. Jura 32° 17' 08" 73° 48' 22" 51. Nawan Lahore 32° 19' 21" 73° 50' 02" 52. Burj Chattha 32° 18' 37" 73° 49' 59" 53. Manchar Chattha 32° 18' 06" 73° 51' 02" 54. Bara Dari 32° 20' 07" 73° 47' 39" 55. Chhoti Rakh Kalan 32° 20' 24" 73° 48' 19" 56. Rakh Kalan 32° 20' 33" 73° 49' 09" 57. Salhoke Chattha 32° 20' 28" 73° 50' 06" 58. Mandhiala Chattha 32° 20' 12" 73° 51' 49" 59. Joe Ke 32° 20' 16" 73° 53' 27" 60. Jamke Chattha 32° 20' 08" 73° 54' 34" 61. Hassan Wali 32° 19' 32" 73° 53' 42" 62. Bara Pind 32° 19' 46" 73° 55' 10" 63. Tahli da Kot 32° 21' 42" 73° 50' 56" 64. Ratta 32° 21' 53" 73° 53' 15" 65. Lound Pur 32° 21' 41" 73° 54' 35" 66. Sultan Nagar 32° 21' 05" 73° 54' 31" 67. Dharowal Kang 32° 21' 08" 73° 57' 17" 68. Dilawar Cheema 32° 20' 12" 73° 56' 35" 69. Dilawar Cheema Khurd 32° 18' 60" 73° 56' 48" 70. Saroke 32° 21' 24" 73° 59' 10" 71. Khanke 32° 23' 56" 73° 58' 27" 72. Faqeeran Wali 32° 22' 18" 73° 58' 11" 73. Ranike Cheema 32° 23' 40" 73° 59' 34" 74. Iftikhar Nagar Cheema 32° 20' 17" 73° 59' 20" 75. Peer Kot 32° 19' 31" 73° 59' 25" 76. Kalu Cheema 32° 19' 05" 73° 58' 55" 77. Ahmed Nagar Chattha 32° 18' 50" 73° 59' 31" 78. Ghayye Wala 32° 15' 48" 73° 59' 34" 79. Jamu Dera 32° 14' 47" 73° 59' 26" 80. Ladhewala Cheema 32° 16' 46" 74° 01' 03" 81. Kalsake 32° 14' 24" 74° 01' 18" 82. Kot Qazi West 32° 13' 55" 74° 01' 50" 83. Kot Jahangir 32° 13' 23" 74° 00' 22" 84. Kot Qadir Bakhash 32° 15' 35" 74° 01' 43" 85. Hassan Wali 32° 16' 11" 74° 01' 03" 86. Chabba Cheema 32° 18' 52" 74° 00' 48" 87. Kale Wala 32° 18' 12" 74° 02' 41" 88. Gil Wala 32° 17' 24" 74° 02' 51" 89. Panjgrain 32° 19' 23" 74° 03' 42"
xii
90. Chak Pathan 32° 18' 57" 74° 04' 45" 91. Adal Garh 32° 18' 43" 74° 05' 50" 92. Banke Cheema 32° 17' 34" 74° 05' 30" 93. Kot Nura 32° 17' 58" 74° 07' 29" 94. Pir Kot 32° 18' 43" 74° 07' 10" 95. Ghakhar 32° 08' 07" 74° 08' 47" 96. Nat Kalan 32° 18' 32" 74° 10' 04" 97. Ojla Kalan 32° 20' 15" 74° 08' 16" 98. Jeune Wali 32° 21' 29" 74° 00' 07" 99. Kheue Wali 32° 21' 25" 74° 01' 01" 100. Kaka Kolo 32° 20' 25" 74° 00' 40" 101. Mansoor Wali 32° 22' 45" 74° 00' 23" 102. Kot Jaffar 32° 23' 09" 74° 02' 11" 103. Kathore Kalan 32° 22' 52" 74° 01' 24" 104. Thatt 32° 22' 05" 74° 02' 19" 105. Gunian Wal 32° 22' 40" 74° 02' 56" 106. Bharoke Cheema 32° 22' 30" 74° 04' 17" 107. Ali Nagar 32° 24' 57" 74° 05' 16" 108. Veroke 32° 24' 16" 74° 06' 38" 109. Dhaunkal 32° 24' 30" 74° 08' 31" 110. Kot Khizri 32° 22' 58" 74° 07' 52" 111. Katla Piran 32° 26' 57" 74° 08' 09" 112. Gakka Mittar 32° 26' 19" 74° 08' 54" 113. Chak Satia 32° 27' 07" 74° 09' 24" 114. Sohdra 32° 27' 36" 74° 10' 47" 115. Wazirabad 32° 26' 18" 74° 07' 03"
The entire study area lies between Latitudes of 32° 08' 07" and 32° 27' 36" North and Longitudes of 73° 41' 57" and 74° 10' 47" East. The study area covers approximately 850 Square Kilometres out of a total of 3198 Square Kilometres area of Gujranwala District. It includes 115 villages out of 800 villages of the district.
xiii
Annexure (II)
ANALYSIS OF ORGANOPHOSPHATE PESTICIDES IN THE BLOOD SAMPLES OF AGRICULTURAL WORKERS OF DISTRICT GUJRANWALA, PUNJAB.
Date ………………
Demographic attributes
Name …………… village/tehsil………………………
1. Gender of the respondent? M / F
2. Marital status?
i) Single … iii) Married … iv) Divorced … v) Widowed … 3.What is your age? i)< 20 ii) 21-30 iii)31-40 iv) 41-50 v)51-60 vi) >60
3. What is the highest level of education you have reached?
i)None … ii) Primary (Grade 1-6) iii)Elementary (Grade 7-8) …
iv)secondary Grade 9-10 … v)Higher secondary grade (11-12)
vi)undergraduate grade >12 … Knowledge and practices of pesticides use 1. yes 2. No 3. sometimes 4. Do you have prior information on safety practices? 5. Do you read and understand toxic label present on pesticides containers ? 6. Have you ever used chemicals with instructions in a language you don’t understand? 7. Do you understand the instructions for use? … … 8. Can you always accurately follow the instructions? … 9. Do you use chemical pesticides on your crops? 10. On your crops, do you also use: natural fertilizers? … 11. Does your pesticide use solve your pest problem 12. Does your use of pesticides increase levels of crop production?
xiv
Respondents’ activities while spraying 13. Do you take bath after spraying? 14. Dou you change clothes after spraying? 15. Do you eat while spraying? 16. Do you drink while spraying? 17. Do you smoking while spraying? 18. Do you think pesticides effect the environment?
Personal protective equipment and clothing when spraying 19. Do you wear normal clothes? 20. Do you wear cotton overalls? 21. Do you wear gloves? 22. Do you wear hat? 23. Do you wear boots? 24. Do you wear goggles? 25. Do you wear handkerchief around mouth? 26. Do you wear mask?
Pesticides related acute health problems 27. Have you ever felt any discomfort/illness after pesticide application? 28. Have you ever felt nausea? 29. Have you ever felt vomiting? 30. Have you ever felt headache? 31. Have you ever felt skin irritation? 32. Have you ever felt coughing? 33. Have you ever felt eye irritation?
xv
Annexure (III)
Preparation of 1X working solution
Reagent name Quantity
5X Reaction Buffer one vial (100 mL) stock solution
Deionized water (dH2O) one vial (100 mL)
1X working solution of reaction buffer was prepared by adding 5 mL of 5 X Reaction buffer stock solutions to 20 mL of deionized water (dH2O). This 25 mL volume of 1X reaction buffer was sufficient for approximately 100 assays of 200 µL.
Annexure (IV)
Preparation of solution of acetylcholine
Reagent name Quantity
Acetylcholine 50 mg chloride
dH2O 100 mL
100 mM solution of acetylcholine in dH2O was. 5 mg of acetylcholine chloride dissolved in 275 µL of dH2O. This solution should be made fresh before each set of experiments. Because acetylcholine hydrochloride is hygroscopic, the remaining solid should be stored desiccated at -20°C. Note that the concentration of acetylcholine in the stock solution should be considered approximate, since the acetylcholine hydrochloride may have varying amounts of water in the solid.
xvi
Annexure (V)
Preparation of H2O2 working solution
Reagent name Quantity
H2O2 3% 1 vial (2mL)
dH2O 100 mL
20 mM H2O2 working solution was prepared by diluting the 3% H2O2 stock solution into the appropriate volume of dH2O. 20 mM H2O2 working solution was prepared from a 3.0% H2O2 stock solution by diluting 23 µL of 3.0% H2O2 into 977 µL of dH2O. The 20 mM H2O2 working solution be less stable and should be used promptly.
Annexure (VI)
Preparation of stock solution of horseradish peroxidase (HRP)
Reagent name Quantity
Horseradish peroxidase (HRP) one vial (10 mL)
1X Reaction Buffer 100 mL
200 U/mL stock solution of horseradish peroxidase (HRP) was prepared by dissolving the contents of the vial of HRP in 1.0 mL of 1X Reaction Buffer. After use, the remaining solution was divided into small aliquots and stored frozen at -20°C.
xvii
Annexure (VII)
Preparation of stock solution of choline oxidase
Reagent name Quantity
Choline oxidase 1 vial (2mL)
1X Reaction Buffer 100 mL
20 U/mL stock solution of choline oxidase was prepared by dissolving the contents of the vial of choline oxidase (Component F) in 600 µL of 1X Reaction Buffer. After use, the remaining solution was divided into small aliquots and stored frozen at -20°C.
Annexure (VIII)
Preparation of 20 mM stock solution of the Amplex Red reagent
Reagent name Quantity
Amplex Red reagent one vial (2mL)
DMSO one vial (2mL)
Warm the one vial of the Amplex Red reagent and DMSO to room temperature. Dissolve the contents of the vial of Amplex Red reagent (1 mg) in 200 µL DMSO. Each vial of Amplex Red reagent was sufficient for approximately 100 assays of 200 µL each. Stored this stock solution at -20°C and protect it from light.
xviii
Annexure (IX)
Preparation of stock solution of acetylcholinesterase
Reagent name Quantity
Acetylcholinesterase 500 U/mL
1X Reaction Buffer 100 mL
100 U/mL stock solution of acetylcholinesterase was prepared by dissolving the contents of the vial of acetylcholinesterase in 600 µL of 1X Reaction Buffer. After use, the remaining solution was divided into small aliquots and stored frozen at -20°C.
Annexure (X)
Calculation of concentrations by using standard curve on Excel sheet Step 1. After Optical Densities (ODs) have been collected, enter each standard OD into a worksheet Step 2. Take the averages of the duplicate values either by adding them up and dividing by two on a calculator, or entering the formula =AVERAGE(A2;B2). Note: change the cell location from A2 and B2 to the desired cell location of each Standard OD. Step 3. Enter the Standard concentrations that each OD should represent next to their corresponding OD average. Creating a Standard Curve Step 1. Highlight your data range and click on the "Chart Wizard" icon in the excel tool bar. Step 2. Choose XY (Scatter) and click "Next" Step 3. Click on "Series" located at the top of the Chart Wizard Window.
xix
Make sure that your X Values are your concentrations and your Y values are your Average OD values. Name your Series or add another Series if you want to compare Standard Curves Click "Next" Step 4. Add information to your chart such as titles and axis labels. Once you customize the chart to your preferences, click "Next". Step 5. Place your chart on a new Excel sheet or insert into your current worksheet. Step 6. Double click on the x-acis values and a "Format Axis" window will pop up. Click on the "Scale" tab on the top of the window. Check the "logarithmic scale" box. Step 7. Do the same to the y-axis Step 8. Highlight data points by clicking on one of them. Click on the "Chart" tab and on the top menu bar click on "Add Trendline". Step 9. A "Add Trendline" window will appear. Select Linear under "Trend/Regression type". Step 10. Go to the "Options" tab on the top of the window and Select "Display equation on chart" and "Display R-squared value on chart" Step 11. Click "OK" to view your chart with equations.
Annexure (XI)
PPM = parts per million
PPM is a term used in chemistry to denote a very, very low concentration of a solution. One gram in 1000 ml is 1000 ppm and one thousandth of a gram (0.001g) in 1000 ml is one ppm.
One thousanth of a gram is one milligram and 1000 ml is one liter, so that 1 ppm = 1 mg per liter = mg/Liter.
xx
PPM is derived from the fact that the density of water is taken as 1kg/L = 1,000,000 mg/L, and 1mg/L is 1mg/1,000,000mg or one part in one million.
1 ppm = 1mg/l = 1ug /ml = 1000ug/L ppm = ug/g =ug/ml = ng/mg = pg/ug = 10 -6 ppm = mg/litres of water
1 gram pure element disolved in 1000ml = 1000 ppm
PPB = Parts per billion = ug/L = ng/g = ng/ml = pg/mg = 10 -9
Making up 1000 ppm solutions
Dilution Formula = M1V1 = M2V2
Reqired ppm x req vol ------= no of mLs for req vol stock e.g. Make up 50 mls vol of 25 ppm from 100 ppm
25 x 50 / 100 = 12.5 mls. i.e. 12.5 mls of 100 ppm in 50 ml volume will give a 25 ppm solution
Serial dilutions
Making up 10-1 M to 10-5 M solutions from a 1M stock solution. Pipette 10 ml of the 1M stock into a 100 ml volumetric flask and make up to the mark to give a 10-1 M soln. Now, pipette 10 ml of this 10-1 M soln. into another 100 ml flask and make up to the mark to give a 10-2 M soln. Pipette again, 10 ml of this 10-2 M soln. into yet another 100 ml flask and make up to mark to give a 10-3 M soln. Pipette a 10 ml of this 10-3 M soln. into another 100 ml flask and make up to mark to give a 10-4 M soln. And from this 10-4 M soln. pipette 10 ml into a 100 ml flask and make up to mark to give a final 10-5 M solution.
Molarity to ppm
Convert molar concentration to grams per liter (Molarity x Atomic mass of solute), then convert to milligrams per liter (ppm) by multiplying by 1000.
Molarity (M) x Atomic mass (At Wt) = grams per liter (g/L) Atomic Mass (Wt.)
PPM to Molarity
Convert ppm to gram based or milligram based concentration.
xxi ppm = 1 mg solute per liter solution or ppm = 0.001 gram per liter solution
Ppm (parts per million) to % (parts per hundred)
Divide the ppm amount by 1,000,000 and multiply by 100 to get %. e.g:
1 ppm = 1/1,000,000 = 0.000001 = 0.0001%
10 ppm = 10/1,000,000 = 0.00001 = 0.001%
100 ppm = 100/1,000,000 = 0.0001 = 0.01%
200 ppn = 200/1,000,000 = 0.0002 = 0.02%
5000 ppm = 5000/1,000,000 = 0.005 = 0.5%
10,000 ppm = 10000/1,000,000 = 0.01 = 1.0%
20,000 ppm = 20000/1,000,000 = 0.02 = 2.0%
Parts per hundred) % to ppm
Divide the % value by 100 and multiply by 1,000,000 to get ppm. e.g. :
1% =0.01 x 1,000,000 = 10,000 ppm
0.5% =0.0.005 x 1,000,000 = 5,000 ppm
0.1% =0.001 x 1,000,000 = 1,000 ppm
0.01% = 0.0001 x 1,000,000 = 100 ppm
Annexure (XII)
Table of PCR Condition
Temperature (˚C) Duration Number of cycles
94˚C 4 minutes 93˚C 0.3 second 45 cycles 59˚C 1 minute 72˚C 45 seconds 72˚C 7 minutes 1 cycle
4˚C 30 minutes 1 cycle
xxii
Annexure (XIII)
Charactersitics of sample population.
Age Male Total Female Total group Sprayer Non sprayers 200 Sprayers Non sprayers 100 (N=150) (N=50) (N=50) (N=50) <20 18(12%) 05(10%) 23(11.5%) 05(10%) 05(10%) 10(10%) 21-30 25(16.6%) 11(22%) 36(18%) 05(10%) 10(20%) 15(15%) 31-40 39(26%) 13(26%) 52(26%) 16(32%) 14(28%) 30(30%) 41-50 51(34%) 13(26%) 64(32%) 15(30%) 13(26%) 28(28%) 51-60 13(8.6%) 06(12%) 19(9.5%) 07(14%) 06(12%) 13(13%) >60 04(3.05%) 02(4%) 06(03%) 02(04%) 02(04%) 04(04%)
Annexure (XIV)
Educational level of workers by gender.
Male Total Female Total Sprayer Non 200 Sprayers Non 100 (N=150) sprayers (N=50) sprayers (N=50) (N=50) Non educated 67(44.6%) 3(6%) 70(35%) 5(10%) 6(12%) 11(11%)
Primary 39(26%) 8(16%) 47(23.5%) 17(34%) 13(26%) 30(30%) grade(1-5) Elementary 28(18.6%) 13(26%) 41(20.5%) 13(26%) 9(18%) 22(22%) grade (6-8) Secondary 9(6%) 16(32%) 25(12.5%) 10(20%) 12(24%) 22(22%) grade (9-10) Higher 5(3.3%) 9(18%) 14(7%) 4(8%) 07(14%) 11(11%) secondary grade(11-12) Undergraduate 2(1.33%) 1(2%) 03(1.5%) 1(2%) 2(4%) 3(3%) grade (>12)
xxiii
Annexure (XV)
Awareness and practices of pesticides use by gender
Male sprayers (N= 150) Female sprayers (N= 50) Yes No Yes No Info about safety 129 (86 %) 21 (14 %) 44(88%) 6(12%) Read and understand toxic 22(15%) 128 (85 %) 5(10%) 45(90%) label on pesticide container Understand 61(40.9%) 89(59.3 %) 14(28%) 36(72 %) instruction for Use of chemical Accurately 42(26.8%) 108(72%) 21(42%) 29(58%) follow instruction Use of chemical 123(82%) 27 (18%) 11(22%) 39(77%) fertilizers Use of natural 128(85%) 22 (15%) 31(62%) 19(38%) fertilizers Pesticides 123(82%) 27 (18%) 42(84) 16(32 %) increase level of crop production Care of wind 105(70%) 45 (30%) 32(64%) 18(36%) direction while spraying
Annexure (XVI)
Personal equipment and clothing while spraying
Male sprayers (N= 200) Female sprayers (N= 100) Yes No Yes No Wearing normal 145(96.6%) 5(4.0%) 49(98%) 1(2%) clothes Wearing cotton 44(29.5%) 106(70.5%) 14(28%) 36(72.0%) overalls Wear gloves 25(16.5%) 125(83.5%) 16(32%) 34(68%) Wear hats 57(38%) 93(62%) 29(58%) 21(42%) Wear boots 102(68.0%) 48(32.0%) 21(42%) 29(58%) Wear 46(31%) 104(69%) 14(28%) 36(72%) glasses/googles /spectacles Wear 63(42%) 87(58%) 15(30%) 35(70%) handkarcheif around mouth Wear mask 19(12.5%) 131(87.0%) 3(6%) 47(94%)
xxiv
Annexure (XVII)
Pesticides related acute health problems
Male sprayers (N= 150) Female sprayers (N= 50) Yes No Yes No Feeling 131(87 %) 19 (13%) 40(80%) 10(20%) discomfort/illness after pesticides application Feeling nausea 102 (68.%) 48 (32.0%) 34(68%) 16(32%) Feeling vomiting 33(22.0 %) 117 (78%) 21(42%) 29(58%) Feeling headache 21 (32.0 %) 129 (68.0%) 29(58%) 22(44%) Feeling skin 21 (32.0%) 136 (68.0%) 14(28%) 36(72%) irritation Feeling eye 70 (46.6%) 80 (53%) 27(56%) 23(46%) irritation Arithritis 20 (13.3%) 130 (86.6%) 19(38%) 31(62%) Backache 25 (17.3 %) 125 (83.6%) 21(42%) 29(58%) Feeling coughing 68 (45.0 %) 82 (55%) 15(30%) (35)70
xxv
List of Publication
Article accepted for Publication
Riaz, S., Manzoor, F., Mahmood, N. and Shahid, S. 2016. Molecular detection of M. tuberculosis & M. bovis and hematological & biochemical analyses in agricultural sprayers exposed to pesticides: a cross sectional study in Punjab, Pakistan during 2014-2016. Journal Of Exposure Science And Environmental Epidemiology, 19 December, 2016. (acceptance letter is attached)
Abstract in Proceedings
Riaz, S., Manzoor, F. and Memona, H. Pesticides exposure, Risk assessment and health problems among pesticides exposed workers of district Gujranwala. In procedding of 35th Pakistan congress of zoology (international) held on March 1-4, 2015 at Karachi University.